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How Learning Works: Seven Research-Based Principles for Smart Teaching
Praise for How Learning Works "How Learning Works is the perfect title for this excellent book. Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning."
--Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching
"This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching."
--Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education
"Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues."
--Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching
"As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book."
--From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning
--Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching
"This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching."
--Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education
"Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues."
--Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching
"As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book."
--From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning
336 pages, Hardcover
First published April 16, 2010
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August 10, 2017
The 7 principles are...
1-prior knowledge (misinformation and otherwise) affects student learning. Consider pre-tests that ask them to use the skills you assume are prerequisite. Prior knowledge should be activiated, sufficient, appropriate and accurate
2-How student organize knowledge matters. Help students to clump information together. For example "part of the writing process," "Enlightenment philosophers," etc.
3-Students have varying degrees of motivation with the material. Help students to see the value of the work, develop their sense of efficacy, and make sure the environment is supportive. Tap into students' future lives and current interests. Create authentic real-world tasks.
4-Help students develop mastery. At the beginning, it will be very conscious, while for us it might be unconscious to do these tasks. Consciously prep them for transfer
5-Feedback matters. "effective feedback can tell students what they are or are not understand, where their performance is going well or poorly, and how tjeu sjpid; direct their subsequent efforts" (137)
6-Cultivate a productive class climate by making resisting a single right answer and connecting personally with students.
7-Students can become self directed learners as they learn to evaluate their strengths and weaknesses and make revisions to their strategies based on those evaluations. Encourage reflection and planning through activities and projects.
1-prior knowledge (misinformation and otherwise) affects student learning. Consider pre-tests that ask them to use the skills you assume are prerequisite. Prior knowledge should be activiated, sufficient, appropriate and accurate
2-How student organize knowledge matters. Help students to clump information together. For example "part of the writing process," "Enlightenment philosophers," etc.
3-Students have varying degrees of motivation with the material. Help students to see the value of the work, develop their sense of efficacy, and make sure the environment is supportive. Tap into students' future lives and current interests. Create authentic real-world tasks.
4-Help students develop mastery. At the beginning, it will be very conscious, while for us it might be unconscious to do these tasks. Consciously prep them for transfer
5-Feedback matters. "effective feedback can tell students what they are or are not understand, where their performance is going well or poorly, and how tjeu sjpid; direct their subsequent efforts" (137)
6-Cultivate a productive class climate by making resisting a single right answer and connecting personally with students.
7-Students can become self directed learners as they learn to evaluate their strengths and weaknesses and make revisions to their strategies based on those evaluations. Encourage reflection and planning through activities and projects.
November 8, 2016
I'm reading this text as a graduate student working as a teaching assistant and also teaching my own college-level courses. I think it's an excellent book for conceptualizing about how our students learn and how to approach teaching. I really enjoy the way that it's organized--a scenario before each chapter, followed up by a quick introduction to the concept, then in-depth research to support the concept. It's well researched and a great way for any college-level professor to really start knowing what matters when it comes to teaching.
My two concerns are this: First, not all of the stories seem to match up with the concept introduced. For example, in Chapter 6 the book talks about how important course climate is for student learning. It recounts a story about an unwary economics professor dealing with a battle between students on illegal immigration. While the book makes a fair point that it is important to have a "positive" climate in the class, it fails to underscore the fact that uncomfortable, challenging climates can also contribute to student learning. This particular chapter was so bogged down in attempting to conceptualize how students develop that it seemed to ignore the subject of how a professor can set up the classroom climate itself so that it can be rewarding, challenging, and yes--a little uncomfortable.
This leads to the second problem: some of the concepts were difficult to conceptualize in the classroom. I think this book would have been much more strongly aided by follow-ups to the stories given (did any of these teachers change their practices? Did they notice a remarkable difference in their students?) Unfortunately, it seemed that these stories were just quick attention-getters, but we are left with speculation--both with what was actually going on in the classroom, and with what professors actively did to change their behaviors. It wasn't the strongest approach and left me wondering if there were possible other problems in the classroom contributing to the way students behaved. While it's not always easy to know what kinds of activities would best implement for these kinds of concepts, it would have definitely aided in this area.
My two concerns are this: First, not all of the stories seem to match up with the concept introduced. For example, in Chapter 6 the book talks about how important course climate is for student learning. It recounts a story about an unwary economics professor dealing with a battle between students on illegal immigration. While the book makes a fair point that it is important to have a "positive" climate in the class, it fails to underscore the fact that uncomfortable, challenging climates can also contribute to student learning. This particular chapter was so bogged down in attempting to conceptualize how students develop that it seemed to ignore the subject of how a professor can set up the classroom climate itself so that it can be rewarding, challenging, and yes--a little uncomfortable.
This leads to the second problem: some of the concepts were difficult to conceptualize in the classroom. I think this book would have been much more strongly aided by follow-ups to the stories given (did any of these teachers change their practices? Did they notice a remarkable difference in their students?) Unfortunately, it seemed that these stories were just quick attention-getters, but we are left with speculation--both with what was actually going on in the classroom, and with what professors actively did to change their behaviors. It wasn't the strongest approach and left me wondering if there were possible other problems in the classroom contributing to the way students behaved. While it's not always easy to know what kinds of activities would best implement for these kinds of concepts, it would have definitely aided in this area.
August 5, 2011
There are endless books on teaching, fewer on learning. Still fewer books on learning that are approachable and readily usable by any instructor. This book helps to fulfill the need for the later. Many books focus on activities to use in the classroom (e.g. think pair share, muddiest point) emphasizing successful teaching. Or, they focus on specific skill sets (e.g. writing rubrics, giving feedback) and strategies for improving those skill sets. While there is room for teaching focused texts, we also need learning focused texts.
How Learning Works begins each chapter with two case scenarios of learning problems faced in the typical classroom (e.g. poor performance on an assignment). It then presents a relevant model for understanding the problem and evidence based options for addressing it. Seven chapters include students' prior learning, organization of information, motivation, development of mastery, practice and feedback, student development & classroom climate, and self directed learning.
I suggest reading the book ready to take notes. I made over a dozen changes to courses I teach with the ideas presented.
I'll be adding this to my "What you may want for your library" list for new instructors.
How Learning Works begins each chapter with two case scenarios of learning problems faced in the typical classroom (e.g. poor performance on an assignment). It then presents a relevant model for understanding the problem and evidence based options for addressing it. Seven chapters include students' prior learning, organization of information, motivation, development of mastery, practice and feedback, student development & classroom climate, and self directed learning.
I suggest reading the book ready to take notes. I made over a dozen changes to courses I teach with the ideas presented.
I'll be adding this to my "What you may want for your library" list for new instructors.
November 10, 2022
Wish someone has given this to me my first year teaching!!
January 27, 2021
This is a pretty standard entry in the genre of "how to improve your work skills" books. Some people really like these books. I don't.
Granted, there's plenty of good stuff in here if you're a teacher or plan to go into teaching, especially at the college level, and like other books that will tell you how to be a better writer or marketer or communicator or networker or fundraiser or office manager, it does the job it intends to do. But like those other books, it does so in a fairly boring, predictable way. Each chapter comes with a couple of case studies, a dry rundown of the latest research on that particular topic, followed by a list of strategies to implement based on the findings of that research. Rinse, repeat.
So this gets two stars from me. It's OK. It does the job. It gave me some ideas to use if I end up teaching some day. But it's not a particularly interesting or well-written book.
Granted, there's plenty of good stuff in here if you're a teacher or plan to go into teaching, especially at the college level, and like other books that will tell you how to be a better writer or marketer or communicator or networker or fundraiser or office manager, it does the job it intends to do. But like those other books, it does so in a fairly boring, predictable way. Each chapter comes with a couple of case studies, a dry rundown of the latest research on that particular topic, followed by a list of strategies to implement based on the findings of that research. Rinse, repeat.
So this gets two stars from me. It's OK. It does the job. It gave me some ideas to use if I end up teaching some day. But it's not a particularly interesting or well-written book.
April 14, 2018
I learned a lot from this book. It's a clearly-written, straightforward, practical approach to how to better facilitate student learning.
January 22, 2022
Accessible, clear, and generally quite useful, "How Learning Works" offers a collection of advice for those teaching. While geared towards university-level instruction, the principles are broadly applicable at all levels.
I appreciated several things about this book. First and foremost, the authors were quite direct in pulling out advice and recommendations both in the body text and at the end of each chapter. Some of this advice might seem straightforward (e.g., use scaffolding when introducing concepts), but is certainly not common knowledge among all professors and is always worth reminding.
I found the chapters on how students organize knowledge, how they develop mastery, and how practice and feedback can be best structured to be particularly useful... though truthfully all chapters were pretty useful.
The resources included in the back of the book are also useful. Sample rubrics, assignment checklists, peer review instructions, and resources for composing learning objectives are all materials I plan to refer to in the future.
I'll likely get a copy of this book for graduate students I supervise who are hired into academia, and plan to use a few chapters of it within our pedagogy working group for faculty. All in all, a good book!
I appreciated several things about this book. First and foremost, the authors were quite direct in pulling out advice and recommendations both in the body text and at the end of each chapter. Some of this advice might seem straightforward (e.g., use scaffolding when introducing concepts), but is certainly not common knowledge among all professors and is always worth reminding.
I found the chapters on how students organize knowledge, how they develop mastery, and how practice and feedback can be best structured to be particularly useful... though truthfully all chapters were pretty useful.
The resources included in the back of the book are also useful. Sample rubrics, assignment checklists, peer review instructions, and resources for composing learning objectives are all materials I plan to refer to in the future.
I'll likely get a copy of this book for graduate students I supervise who are hired into academia, and plan to use a few chapters of it within our pedagogy working group for faculty. All in all, a good book!
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May 13, 2021Read this for a course I took on pedagogy which I took as part of the "Learning Assistant Program" at my university.
Pretty solid introduction to teaching methods, I've always been on the student end of things so this was a good way to see the instructor's point of view and learn about effective learning. I'll admit I kinda skim read (I tend to do that with assigned reading) so I'm not gonna rate it, but I still found it a valuable read.
Pretty solid introduction to teaching methods, I've always been on the student end of things so this was a good way to see the instructor's point of view and learn about effective learning. I'll admit I kinda skim read (I tend to do that with assigned reading) so I'm not gonna rate it, but I still found it a valuable read.
December 4, 2021
This was a textbook for a pedagogy class, and I read a good chunk of it, but not every single chapter. I’m not the target audience, but as someone who does most of the training at my library, there was still a lot of applicable material.
It’s a little older, but I don’t think the material is the type that becomes outdated very quickly, and the professor for this class was careful and intentional, so I trust her judgment on this choice of textbook.
It’s easy to follow, and I the focus is exactly where it needs to be: the students. There are real-world (or, at least, real-world like) examples of different teaching/learning situations at the beginning of each chapter, responses according to research, and tips for how to apply the principles.
It’s a lot to remember and will work best as a reference to be consulted often until the practices and ideas come more naturally.
It’s a little older, but I don’t think the material is the type that becomes outdated very quickly, and the professor for this class was careful and intentional, so I trust her judgment on this choice of textbook.
It’s easy to follow, and I the focus is exactly where it needs to be: the students. There are real-world (or, at least, real-world like) examples of different teaching/learning situations at the beginning of each chapter, responses according to research, and tips for how to apply the principles.
It’s a lot to remember and will work best as a reference to be consulted often until the practices and ideas come more naturally.
August 8, 2020
Of the required reading this semester, this text was the most approachable. Solid tips and suggestion for use and application in the classroom and other learning environments.
April 29, 2020
I appreciate how strategies that we have been using for a while get broken down into why they work, how they can be more effective, and practical applications for the classroom.
February 12, 2022
Very few books successfully translate educational research into practical implications for practice. This book is one of the rare successes in that regard. The book is based on seven research-based principles that can drive teaching and learning, each expressed in a single sentence. This makes the book's core content easy to remember.
Each chapter of the book poses a question, such as chapter 4, where the question is " How do students develop mastery?". The opening element in each chapter is then a pair of very short, concrete learning stories. The principle which lies behind these contrasting stories is then brought in, and the research behind the principle is explained and cited. The authors then examine the implications of the research and finish each chapter with a set of concrete strategies that can make that principle come alive in the classroom. This format successfully blends theory and practice in a way which means that teachers don't just blindly implement a strategy, but are actually able to adapt classroom strategies to the needs of their situation, since they understand the theory behind them.
I read a lot of original education research and I found this book to be an excellent summary of some of the latest patterns that are emerging from the research. As a teacher educator, I have made use of chapters from the book in professional development activities with teachers. If you want a summary of some of the most important recent research in education and what it means for the classroom, this book is a great starting place.
Each chapter of the book poses a question, such as chapter 4, where the question is " How do students develop mastery?". The opening element in each chapter is then a pair of very short, concrete learning stories. The principle which lies behind these contrasting stories is then brought in, and the research behind the principle is explained and cited. The authors then examine the implications of the research and finish each chapter with a set of concrete strategies that can make that principle come alive in the classroom. This format successfully blends theory and practice in a way which means that teachers don't just blindly implement a strategy, but are actually able to adapt classroom strategies to the needs of their situation, since they understand the theory behind them.
I read a lot of original education research and I found this book to be an excellent summary of some of the latest patterns that are emerging from the research. As a teacher educator, I have made use of chapters from the book in professional development activities with teachers. If you want a summary of some of the most important recent research in education and what it means for the classroom, this book is a great starting place.
July 1, 2014
A good non-fiction book clearly targeted towards those who teach adults like university professors, it collects in 7 chapters problems professors face in their teaching - each chapter starts with two small stories of teaching frustration, goes over to what underlies these problems with students, summarizes the peer-reviewed literature, and shows ways for teachers to alleviate the problem in question.
It's no wonder that organizations like Software Carpentry chose this book for their instructors, it's a great crash-course on how to be a better teacher. If I ever wind up teaching at a university (stranger things have happened) I will be "borrowring" from the appendix of this book with useful templates for feedback etc., and I will have to re-read the entire book, again. It's not that long anyway.
Reading through the chapters I couldn't help but be reminded of my terrible high school years and how the teachers seemed to have actively tried to do everything wrong, with no feedback, one big evaluation at the end of the year instead of small ones, terrible classroom atmosphere, no defined goal of learning, no rubrics, and on and on and on.
I would love to read the same book, but with a different target audience - a book that takes all this peer-reviewed, published and established knowledge about learning and bundles it into a manual on how to learn and study "the best" way(s). It would have helped tremendeously in my high school and university years.
Recommended for: Those who teach, and those who like to learn by themselves and would like to learn more efficiently.
It's no wonder that organizations like Software Carpentry chose this book for their instructors, it's a great crash-course on how to be a better teacher. If I ever wind up teaching at a university (stranger things have happened) I will be "borrowring" from the appendix of this book with useful templates for feedback etc., and I will have to re-read the entire book, again. It's not that long anyway.
Reading through the chapters I couldn't help but be reminded of my terrible high school years and how the teachers seemed to have actively tried to do everything wrong, with no feedback, one big evaluation at the end of the year instead of small ones, terrible classroom atmosphere, no defined goal of learning, no rubrics, and on and on and on.
I would love to read the same book, but with a different target audience - a book that takes all this peer-reviewed, published and established knowledge about learning and bundles it into a manual on how to learn and study "the best" way(s). It would have helped tremendeously in my high school and university years.
Recommended for: Those who teach, and those who like to learn by themselves and would like to learn more efficiently.
August 31, 2014
This is a pretty exhaustive catalog summing up the basic research in instructional psychology that's applicable to faculty across disciplines. While there are plenty of duh studies (did you know that providing your students with clear expectations for an assignment will motivate them because they won't see grading and evaluation as arbitrary???), this work is particularly useful as a gut-check reference. I used it this semester to make sure I had time built in to my courses to effectively help my students learn the most important concepts and all that entails (mastering constituent skills, observing me or someone else model correct approaches, reflect on the assignment, etc.).
What this book does not do, or only hints at with accomplished subtlety, is the academic culture that denigrates teaching, placing it well below research and even service on the list of important-things-that-define-your-career. This has always struck me as absurd and has led, more than any other factor, to my current situation of masquerading on the fringes of the academy unsure of whether to dedicate my life to a career in a field with such skewed priorities.
What this book does not do, or only hints at with accomplished subtlety, is the academic culture that denigrates teaching, placing it well below research and even service on the list of important-things-that-define-your-career. This has always struck me as absurd and has led, more than any other factor, to my current situation of masquerading on the fringes of the academy unsure of whether to dedicate my life to a career in a field with such skewed priorities.
October 11, 2017
Extremely repetitive and really doesn't offer anything novel; a lot of common sense. It is based soundly on research, however, and the book is cleanly organized with practical points highlighted at the end of each chapter. While I did not learn much of anything new from this book, it did strengthen some points for me and helped me hone in on some areas I would want to strengthen in my teaching (it also validated many of the techniques that I already use, which is always a good feeling!). The main problem is simply that there is not enough time in the semester to take the time that is necessary for so much practice and feedback that is needed for effective learning. My main complaint is that this book could be cut in half; it repeats so much and goes on and on with anecdotal examples. Teachers are strapped for time and do not have the luxury of reading unnecessary filler material.
November 19, 2012
Great survey of how to be an effective college-level teacher. Case-studies are excellent, and appendixes help you structure assessments. Terrific guidance on how to articulate learning objectives. The "research-based" principles are helpful for those of us who don't have an ed school background but the book doesn't problematize the methodology which leaves questions about applicability hanging. However, the authors (who have studied pedagogy in fields ranging from stats to biology and physics to anthropology) have tested these methods and provided reflections on these field-tests. That counts for a lot.
February 9, 2016
A teacher teaches so that students can learn. What could be more helpful than for a teacher to know how students learn? What motivates them? What do they bring to the course in terms of their own development and prior knowledge? What are the best ways for them to organize new knowledge, practice new skills, and receive useful feedback? How can a course create an environment that helps or hinders learning?
And why wasn't this book written in 1998 instead of 2010???
And why wasn't this book written in 1998 instead of 2010???
January 16, 2014
What a decent book! I wish more non fiction were written like this (Influence style, but a little lighter).
Alone it's really useful for professors , I wish I could make everybody on my college faculty read it.
Alone it's really useful for professors , I wish I could make everybody on my college faculty read it.
November 14, 2015
Great for understanding pedagogy, the perspectives on learning from the podium. I appreciated the (over-the-top, anonymized) case studies.
November 1, 2016
Sensible, research-backed advice, conveyed with examples from many different academic fields. Probably worth skimming through again before next time I design/teach a course. The conclusion chapter is a nice review, applying each of their 7 principles to the process of learning to teach.
Below are just my notes-to-self. I read this while our department was discussing revisions to the curriculum, especially Intro to Stats. So most of my notes are aimed either at that, or at the Statistical Graphics course I taught before.
(See also co-author Lovett's Thinking with Data for stats edu ideas?)
1: Students' prior knowledge can help or hinder learning.
* p.17: Get students to generate relevant knowledge/examples from their own lives. Garfield et al. 2007 got students to come up with examples from daily life that show high or low variability, and use those examples to reason about variability throughout the course.
* p.23: Carefully activate the *right* prior knowledge, when it could go several competing ways. In a psych class, many students hear "negative reinforcement" and wrongly assume that negative=bad, i.e. it's about punishment. But actually it's negative=subtraction, positive=addition: negative reinforcement removes obstacle to learning. How can we activate the right prior knowledge for often-misused stats terminology, like "significant"?
* p.33: Connect to students' everyday experience. Too often we use stats examples about bespoke measurements in a lab or factory... But where can stat reasoning apply directly in daily life?
* p.37: Correct student misconceptions by asking them to make and test predictions. But how to do this in Intro Stats? The driving question usually isn't, e.g., "How big is the estimated effect?" (which you could predict and test), but rather "Did our study-design estimate this effect *precisely enough*? Is our conclusion *justified*?" It's hard to predict-and-test answers to such epistemological questions.
2: How students organize knowledge influences how they learn and apply what they know.
* p.50: What kind of knowledge-organization structure is good for Intro Stat? Examples here are hierarchies, densely-connected webs, long chains, etc. For current Intro Stat, with its barrage of tests, we have flowcharts ("If DV is such and IVs are such, use that test"). But this structure *obscures* the similarities between what each test is trying to do. Maybe simulation-based or permutation-test-based Intro Stat could have a more-helpful knowledge-organizing structure?
* p.64: Use a sorting task to see how students are organizing their knowledge. Give them a set of problems with some superficial and some deep connections, and ask them to group similar things together. I wonder how Intro Stat students would sort a list of statistical tests? Exam questions? Statistical concepts? And how do we *wish* they would cluster them?
3: Students' motivation generates, directs, and sustains what they do to learn.
* p.80: Nice breakdown of levers we can use to affect students' motivation. Have we made the *environment* supportive? Have we convinced them of their *efficacy* (it's possible to learn / do well if I work at it)? Have we convinced them of the *value* of this learning goal?
* p.83: The authors suggest "authentic, real-world tasks," although math teacher / blogger Dan Meyer has good caveats suggesting this isn't the right axis. You can't just slap "real" context on a fake question; better to find a sincerely-felt, intellectually-motivating question, even if it's not "real-world."
* p.85: I was glad to see I'm already using most of their "strategies that help students build positive expectancies"... Align objectives, assessments, and instruction; aim for appropriate levels of challenge; give early success opportunities; make clear expectations, provide rubrics, and be fair; give targeted feedback...
* p.89: Reflection is good! Ask students to reflect on what they learned from the task (value of the work), or how they prepared for the task and what skills they need to work on (efficacy).
4: To develop mastery, students must acquire component skills, practice integrating them, and know when to apply what they have learned.
* p.105: Do your best to reduce cognitive load, teaching one task at a time---not several at once. The example here is a caution for our Intro Stats redesign: it suggests teaching new math and a new computer skill separately, instead of at once. We considered teaching basic programming (as part of a simulation-based inference approach) alongside intro stats concepts, but that might be too much. On the other hand... we already teach them new point-and-click software, and "review" math concepts that many never learned well; so they probably *already* have cognitive overload. Maybe teaching coding wouldn't be that different in terms of cognitive load.
Of course, you do want them to integrate skills eventually. But (1) don't overload them so much they can't even learn the components first, and (2) teach & evaluate the integration as its own skill.
* p.110: Exciting to see an old study, by Schoklow and Judd (1908?), using my alma mater Olin College's favorite pedagogical idea: do-learn. Get concrete hands-on experience in particular contexts, and combine that with abstract knowledge, instead of using just one or the other.
Also, use "structured comparisons": Don't just say "analyze each of these business cases," but ask them to compare cases too. This forces the students to think about abstract features they can compare across cases.
* p.114: Diagnose weak component skills early in the semester. Give them a self-diagnostic exam; provide specific recommended resources for each component if students need to brush up; review some of the components as a class if many people are underprepared. I wish some of my grad-level courses had done this, instead of dropping implicit pre-reqs on us midway through the semester.
* p.119: Two good ways to build practice questions for class discussion (or think-pair-shares) or even homeworks: Give students a context and ask for relevant skills; and vice versa. For example, here's a scientific question; what stat concepts and tools would be relevant? Or, here's a statistical test; make up some contexts in which this would be useful.
Even more advice for writing think-pair-share questions: Where does this skill apply? What is the broader principle behind this idea? Compare these cases and find common deep features. Where have we seen a similar concept used before?
5: Goal-directed practice coupled with targeted feedback are critical to learning.
* p.126: Cycle through many small practice-feedback iterations, not just one big project / "waterfall process." In the summer undergrad research project that I helped to TA, I wish we'd designed the tasks to allow for more of these small iterations. I tried to do this with my team---let's first build the simplest model we can think of, and evaluate it; now let's build on it, revise the model, and compare its performance to the old model---but I wish it had been explicitly modeled throughout the program.
* p.129: I've heard the advice to use "active language" when writing learning objectives. Here's why: It's easier for the student (and yourself) to monitor and evaluate performance when the goal is explicitly something you can do. If I want you to "understand concept X," it's unclear how we can tell whether this is met. But if my goal is for you to "apply this concept to solve problems" or "recognize when this concept applies to an issue," then the student can self-monitor during their studying; and I can evaluate fairly.
* p.132: Intriguing idea called Vygotsky's Zone of Proximal Development: optimal level of challenge is "a task that the student cannot perform successfully on his or her own but could perform successfully with some help from another person or group." Good advice for someone like myself, with strong "I have to do it myself!" soloist tendencies. Not only that, but when students teach each other, they also learn by being in the teacher-role, not just in the student-role. Also a good lens to view designing and evaluating group projects. Ties to the research reported in Whistling Vivaldi: And Other Clues to How Stereotypes Affect Us and to my attempts at starting a dissertation-writing group with my PhD cohort.
Finally, makes me wonder: can I scaffold, or make a rubric for, my own thesis work?
* p.135: Again, reflection is good! Remind yourself of how much you've learned. At the start, of course progress is slow, because you don't have the foundations yet; but it's *also* slow at the "end" when you are quite advanced, because the remaining things to learn are the hardest ones. Instead of feeling stuck there, take time to remind yourself of how much you learned in the middle stage, and how your expectations/criteria for improvement should adjust to where you are in the process.
* p.140: Yes, give targeted feedback, but *be concise*! Just the big ideas---don't overwhelm with detailed margin notes on every typo. In the latter case, they'll either be overwhelmed by the list of things to do; or they'll focus their energy on the easy-fixes and ignore the big ideas.
* p.151: Ask students to report how they used feedback. Like the journal review cycle :) where the editor wants to see responses to reviewers' comments, not just the revised draft itself. This'll help students see the full learning cycle across assignments and revisions.
6: Students' current level of development interacts with the social, emotional, and intellectual climate of the course to impact learning.
* p.157: Students' social+emotional gains during college are often greater than their intellectual gains over that time. That was true for me too. So be mindful that academics aren't the only reason they're here, nor the only stress they're undergoing.
* p.163: They list 4 stages of intellectual development.
Duality: knowledge is divided into right and wrong, without ambiguity. Just give me the right facts and test whether I memorized them.
Multiplicity: knowledge is just opinion, and everybody has their own. Everything's subjective, so my opinion should get as good a grade as any other.
Relativism: not all opinions are equal; there are both general and discipline-specific rules of evidence for evaluating opinions/knowledge. Help me see how to interact critically with the content.
Commitment: I choose one of these competing theories/opinions "as a foundation to build on, refining it as they go," as a "nuanced and informed" choice.
(I've also heard cartoonish view of this, aka Frosh-Soph-Junior-Senior:
"Ignorant + unaware" >> "Ignorant + aware" >> "Knowledgeable + unaware" >> "Knowledgeable + aware")
* p.164: So, the 3rd stage above *is* (in a sense) the core of statistical thinking that we try to teach freshmen in Intro Stat. We're not trying to teach them a set of facts, but a set of tools for evaluating evidence. Yet if most students only come in at the 1st stage, they're nowhere near ready for the 3rd stage when they take Intro Stat. Is that why the course has historically been a list of statistical tests to memorize---because that's all you can reasonable *expect* from the students? Is there a better way to teach it at that level?
* p.166: Research suggests that many students leave college only at the 2nd stage above. Oof. Maybe better than staying at 1st stage? But 2nd stage seems "valuable" primarily as a stepping-stone to 3rd. Stopping at 2nd leaves you as that annoying guy who responds to everything with "That's just your opinion, man."
* p.168: Look into suggested book here, "Why Are All The Black Kids Sitting Together in the Cafeteria?": A Psychologist Explains the Development of Racial Identity.
* p.171-2: Be aware of your course climate. Obviously don't be explicitly marginalizing (hostile and discriminatory). Also try not to be implicitly marginalizing, with unintended off-putting messages. Better is implicitly centralizing: if a marginalized perspective happens to come up, treat it in a validating way (like the econ student asking to view the case study through a racial lens, and prof saying it's a valid point so let's dig deeper). Best is explicitly centralizing: not *just* validating students who risk bringing up these perspectives, but intentionally integrating those perspectives into the course (by instructor). Also set discussion ground rules "to foster sensitivity to the perspectives that students bring to the classroom." What can I do to be explicitly inclusive in an Intro Stats class? Perhaps bring up recent news reports about algorithmic bias and address those problems head-on? It feels kind of superficial to point out a few female / minority statisticians; I don't want to leave it at that; but maybe it's worse if I don't even bother to do that?
* p.178: Faculty-student interaction is a key part of the learning environment. Better interaction can mean more contact overall; contacts that feel "real" and not just formalized or superficial; responsiveness in the classroom; treating students as individuals... It leads to better retention (at the school and in the particular department/field), more students going to grad school, and better learning outcomes.
* p.179: Several stages of transforming a curriculum. Exclusive: shows just one dominant perspective (e.g. if the only music appreciation course offered is Classical Music By Great Old Dead White Men). Exceptional Outsider: adds "a token marginalized perspective" (e.g. one Native American poet in a course on US poetry). Transformed: integrates multiple perspectives at the core.
Again, seems clearer in arts and humanities, but what about stats? They say that if such-and-such professor "had systematically highlighted the contributions of engineers who happen to be women, this would have communicated powerful messages about women in engineering." That sounds doable in stats; there are many respected non-white-guy statisticians and I have had many such colleagues. But also, many female and minority students leave science for "fields where race and gender are legitimate lenses of analysis." I have lots more work to do in understanding how this applies to stats.
* p.180: Ways to promote student development and a good climate: Validate different views, make uncertainty safe, remind them that we want to embrace complexity and not oversimplify. Don't tokenize, asking a minority student to speak for their whole group. Learn students' names and help them learn each other's. (One prof requires that students sign up for small-group meetings with him in first couple of weeks, 3-ish students at a time, so he can get to know them a bit and learn their names from the start). Reinforce group rules for productive discussions---see Appendix E. If you ask someone to sit in and give feedback on your teaching, ask about course climate too.
7: To become self-directed learners, students must learn to assess the demands of the task, evaluate their own knowledge and skills, plan their approach, monitor their progress, and adjust their strategies as needed.
* p.192: I've never seen the point of concept maps, but the authors illustrate how they might help some learners in specific cases. Consider a student who just highlighted textbooks and memorized facts to get good grades in high school. Now, concept maps could help him transition if he's having trouble with college-level classes.
* p.194: Students with "a generic writing-as-knowledge-telling strategy ... presented everything that they knew about the paper's topic without regard to the specific goal or purpose of the assignment." (I admit I do this myself in early paper drafts, including my thesis proposal!) Again, you'll have to scaffold and hand-hold a bit, to help students transition from high-school expectations to college-level ones. Remind them to assess the task itself carefully.
* p.198: "...students who naturally monitor their own progress and try to explain to themselves what they are learning along the way generally show greater learning gains... Students who were taught or prompted to monitor their own understanding or to explain to themselves what they were learning had greater learning gains..." So, how can we teach students to self-monitor? I guess we can start by just prompting them often?
* p.207: You can scaffold a complex assignment by laying out a detailed plan with interim deadlines and deliverables... modeling the planning process for them... but after they have some experience, you can *also* ask them to make their own plan, so that this plan itself is a deliverable (and give them feedback on it).
* p.208: Teach students, or have them come up with, simple heuristics for self-checking. It should be possible to make a cheat-sheet of simple heuristics for Intro Stats; e.g., probabilities and variances should always be non-negative.
* p.209: Require students to do guided self-assessements: maybe they have to assess their own work against my rubric before submitting it for grading. Also ask them to reflect on and annotate their work process, e.g. in my Stat Graphics class they could keep a "process log" describing the iterations of their poster design and why they made certain design choices.
* p.211: Use "exam wrappers" (see also Appendix F). This is a short sheet to fill in when the exams are handed back, asking what mistakes they made; how they studied; and what they'll do differently to prepare better next time. Again, enforces reflection and planning.
* p.214: Model your own process for them, live. Show them how you assess the task, assess yourself, make a plan, monitor your own progress, reassess and readjust as you go, and evaluate final product. Especially for younger students, it helps to see that experts have to reassess too.
Appendices
* A: Self-assessments. Examples of multiple-choice questions for gauging a student's level of familiarity with a concept or tool.
* B: Concept maps. Again, I can't recall ever using these productively, but YMMV.
* C: Rubrics. Remember to include a category for "Mechanics" or similar (typos, proper citations, etc.), else it's not really fair to grade them.
* D: Learning objectives. Don't be too high-level; break down into its component skills: "problem solving may require defining the parameters of the problem, choosing appropriate formulas, and so on."
* E: Ground rules. If using these, establish them at start of the course, explain their purpose, get students' agreement, and hold students accountable. (Examples: Critique ideas, not people. Do not monopolize discussion. Use laptops only for legit class activities.) Also, step-by-step process for having students create their own ground rules---could be very useful for a discussion-heavy class.
* F: Exam wrappers. Example questions: How much time did you spend preparing? What percent of that time was spent on... (reading book for 1st time; reviewing homeworks; etc...)? What percent of points lost was for... (concept)? How will you prep next time?
* G: Checklists. (Could use rubrics for this? Attach to turned-in HW, checking off each part you did?)
* H: Peer review. Oddly specific instructions, but good Qs to reflect on & report.
Below are just my notes-to-self. I read this while our department was discussing revisions to the curriculum, especially Intro to Stats. So most of my notes are aimed either at that, or at the Statistical Graphics course I taught before.
(See also co-author Lovett's Thinking with Data for stats edu ideas?)
1: Students' prior knowledge can help or hinder learning.
* p.17: Get students to generate relevant knowledge/examples from their own lives. Garfield et al. 2007 got students to come up with examples from daily life that show high or low variability, and use those examples to reason about variability throughout the course.
* p.23: Carefully activate the *right* prior knowledge, when it could go several competing ways. In a psych class, many students hear "negative reinforcement" and wrongly assume that negative=bad, i.e. it's about punishment. But actually it's negative=subtraction, positive=addition: negative reinforcement removes obstacle to learning. How can we activate the right prior knowledge for often-misused stats terminology, like "significant"?
* p.33: Connect to students' everyday experience. Too often we use stats examples about bespoke measurements in a lab or factory... But where can stat reasoning apply directly in daily life?
* p.37: Correct student misconceptions by asking them to make and test predictions. But how to do this in Intro Stats? The driving question usually isn't, e.g., "How big is the estimated effect?" (which you could predict and test), but rather "Did our study-design estimate this effect *precisely enough*? Is our conclusion *justified*?" It's hard to predict-and-test answers to such epistemological questions.
2: How students organize knowledge influences how they learn and apply what they know.
* p.50: What kind of knowledge-organization structure is good for Intro Stat? Examples here are hierarchies, densely-connected webs, long chains, etc. For current Intro Stat, with its barrage of tests, we have flowcharts ("If DV is such and IVs are such, use that test"). But this structure *obscures* the similarities between what each test is trying to do. Maybe simulation-based or permutation-test-based Intro Stat could have a more-helpful knowledge-organizing structure?
* p.64: Use a sorting task to see how students are organizing their knowledge. Give them a set of problems with some superficial and some deep connections, and ask them to group similar things together. I wonder how Intro Stat students would sort a list of statistical tests? Exam questions? Statistical concepts? And how do we *wish* they would cluster them?
3: Students' motivation generates, directs, and sustains what they do to learn.
* p.80: Nice breakdown of levers we can use to affect students' motivation. Have we made the *environment* supportive? Have we convinced them of their *efficacy* (it's possible to learn / do well if I work at it)? Have we convinced them of the *value* of this learning goal?
* p.83: The authors suggest "authentic, real-world tasks," although math teacher / blogger Dan Meyer has good caveats suggesting this isn't the right axis. You can't just slap "real" context on a fake question; better to find a sincerely-felt, intellectually-motivating question, even if it's not "real-world."
* p.85: I was glad to see I'm already using most of their "strategies that help students build positive expectancies"... Align objectives, assessments, and instruction; aim for appropriate levels of challenge; give early success opportunities; make clear expectations, provide rubrics, and be fair; give targeted feedback...
* p.89: Reflection is good! Ask students to reflect on what they learned from the task (value of the work), or how they prepared for the task and what skills they need to work on (efficacy).
4: To develop mastery, students must acquire component skills, practice integrating them, and know when to apply what they have learned.
* p.105: Do your best to reduce cognitive load, teaching one task at a time---not several at once. The example here is a caution for our Intro Stats redesign: it suggests teaching new math and a new computer skill separately, instead of at once. We considered teaching basic programming (as part of a simulation-based inference approach) alongside intro stats concepts, but that might be too much. On the other hand... we already teach them new point-and-click software, and "review" math concepts that many never learned well; so they probably *already* have cognitive overload. Maybe teaching coding wouldn't be that different in terms of cognitive load.
Of course, you do want them to integrate skills eventually. But (1) don't overload them so much they can't even learn the components first, and (2) teach & evaluate the integration as its own skill.
* p.110: Exciting to see an old study, by Schoklow and Judd (1908?), using my alma mater Olin College's favorite pedagogical idea: do-learn. Get concrete hands-on experience in particular contexts, and combine that with abstract knowledge, instead of using just one or the other.
Also, use "structured comparisons": Don't just say "analyze each of these business cases," but ask them to compare cases too. This forces the students to think about abstract features they can compare across cases.
* p.114: Diagnose weak component skills early in the semester. Give them a self-diagnostic exam; provide specific recommended resources for each component if students need to brush up; review some of the components as a class if many people are underprepared. I wish some of my grad-level courses had done this, instead of dropping implicit pre-reqs on us midway through the semester.
* p.119: Two good ways to build practice questions for class discussion (or think-pair-shares) or even homeworks: Give students a context and ask for relevant skills; and vice versa. For example, here's a scientific question; what stat concepts and tools would be relevant? Or, here's a statistical test; make up some contexts in which this would be useful.
Even more advice for writing think-pair-share questions: Where does this skill apply? What is the broader principle behind this idea? Compare these cases and find common deep features. Where have we seen a similar concept used before?
5: Goal-directed practice coupled with targeted feedback are critical to learning.
* p.126: Cycle through many small practice-feedback iterations, not just one big project / "waterfall process." In the summer undergrad research project that I helped to TA, I wish we'd designed the tasks to allow for more of these small iterations. I tried to do this with my team---let's first build the simplest model we can think of, and evaluate it; now let's build on it, revise the model, and compare its performance to the old model---but I wish it had been explicitly modeled throughout the program.
* p.129: I've heard the advice to use "active language" when writing learning objectives. Here's why: It's easier for the student (and yourself) to monitor and evaluate performance when the goal is explicitly something you can do. If I want you to "understand concept X," it's unclear how we can tell whether this is met. But if my goal is for you to "apply this concept to solve problems" or "recognize when this concept applies to an issue," then the student can self-monitor during their studying; and I can evaluate fairly.
* p.132: Intriguing idea called Vygotsky's Zone of Proximal Development: optimal level of challenge is "a task that the student cannot perform successfully on his or her own but could perform successfully with some help from another person or group." Good advice for someone like myself, with strong "I have to do it myself!" soloist tendencies. Not only that, but when students teach each other, they also learn by being in the teacher-role, not just in the student-role. Also a good lens to view designing and evaluating group projects. Ties to the research reported in Whistling Vivaldi: And Other Clues to How Stereotypes Affect Us and to my attempts at starting a dissertation-writing group with my PhD cohort.
Finally, makes me wonder: can I scaffold, or make a rubric for, my own thesis work?
* p.135: Again, reflection is good! Remind yourself of how much you've learned. At the start, of course progress is slow, because you don't have the foundations yet; but it's *also* slow at the "end" when you are quite advanced, because the remaining things to learn are the hardest ones. Instead of feeling stuck there, take time to remind yourself of how much you learned in the middle stage, and how your expectations/criteria for improvement should adjust to where you are in the process.
* p.140: Yes, give targeted feedback, but *be concise*! Just the big ideas---don't overwhelm with detailed margin notes on every typo. In the latter case, they'll either be overwhelmed by the list of things to do; or they'll focus their energy on the easy-fixes and ignore the big ideas.
* p.151: Ask students to report how they used feedback. Like the journal review cycle :) where the editor wants to see responses to reviewers' comments, not just the revised draft itself. This'll help students see the full learning cycle across assignments and revisions.
6: Students' current level of development interacts with the social, emotional, and intellectual climate of the course to impact learning.
* p.157: Students' social+emotional gains during college are often greater than their intellectual gains over that time. That was true for me too. So be mindful that academics aren't the only reason they're here, nor the only stress they're undergoing.
* p.163: They list 4 stages of intellectual development.
Duality: knowledge is divided into right and wrong, without ambiguity. Just give me the right facts and test whether I memorized them.
Multiplicity: knowledge is just opinion, and everybody has their own. Everything's subjective, so my opinion should get as good a grade as any other.
Relativism: not all opinions are equal; there are both general and discipline-specific rules of evidence for evaluating opinions/knowledge. Help me see how to interact critically with the content.
Commitment: I choose one of these competing theories/opinions "as a foundation to build on, refining it as they go," as a "nuanced and informed" choice.
(I've also heard cartoonish view of this, aka Frosh-Soph-Junior-Senior:
"Ignorant + unaware" >> "Ignorant + aware" >> "Knowledgeable + unaware" >> "Knowledgeable + aware")
* p.164: So, the 3rd stage above *is* (in a sense) the core of statistical thinking that we try to teach freshmen in Intro Stat. We're not trying to teach them a set of facts, but a set of tools for evaluating evidence. Yet if most students only come in at the 1st stage, they're nowhere near ready for the 3rd stage when they take Intro Stat. Is that why the course has historically been a list of statistical tests to memorize---because that's all you can reasonable *expect* from the students? Is there a better way to teach it at that level?
* p.166: Research suggests that many students leave college only at the 2nd stage above. Oof. Maybe better than staying at 1st stage? But 2nd stage seems "valuable" primarily as a stepping-stone to 3rd. Stopping at 2nd leaves you as that annoying guy who responds to everything with "That's just your opinion, man."
* p.168: Look into suggested book here, "Why Are All The Black Kids Sitting Together in the Cafeteria?": A Psychologist Explains the Development of Racial Identity.
* p.171-2: Be aware of your course climate. Obviously don't be explicitly marginalizing (hostile and discriminatory). Also try not to be implicitly marginalizing, with unintended off-putting messages. Better is implicitly centralizing: if a marginalized perspective happens to come up, treat it in a validating way (like the econ student asking to view the case study through a racial lens, and prof saying it's a valid point so let's dig deeper). Best is explicitly centralizing: not *just* validating students who risk bringing up these perspectives, but intentionally integrating those perspectives into the course (by instructor). Also set discussion ground rules "to foster sensitivity to the perspectives that students bring to the classroom." What can I do to be explicitly inclusive in an Intro Stats class? Perhaps bring up recent news reports about algorithmic bias and address those problems head-on? It feels kind of superficial to point out a few female / minority statisticians; I don't want to leave it at that; but maybe it's worse if I don't even bother to do that?
* p.178: Faculty-student interaction is a key part of the learning environment. Better interaction can mean more contact overall; contacts that feel "real" and not just formalized or superficial; responsiveness in the classroom; treating students as individuals... It leads to better retention (at the school and in the particular department/field), more students going to grad school, and better learning outcomes.
* p.179: Several stages of transforming a curriculum. Exclusive: shows just one dominant perspective (e.g. if the only music appreciation course offered is Classical Music By Great Old Dead White Men). Exceptional Outsider: adds "a token marginalized perspective" (e.g. one Native American poet in a course on US poetry). Transformed: integrates multiple perspectives at the core.
Again, seems clearer in arts and humanities, but what about stats? They say that if such-and-such professor "had systematically highlighted the contributions of engineers who happen to be women, this would have communicated powerful messages about women in engineering." That sounds doable in stats; there are many respected non-white-guy statisticians and I have had many such colleagues. But also, many female and minority students leave science for "fields where race and gender are legitimate lenses of analysis." I have lots more work to do in understanding how this applies to stats.
* p.180: Ways to promote student development and a good climate: Validate different views, make uncertainty safe, remind them that we want to embrace complexity and not oversimplify. Don't tokenize, asking a minority student to speak for their whole group. Learn students' names and help them learn each other's. (One prof requires that students sign up for small-group meetings with him in first couple of weeks, 3-ish students at a time, so he can get to know them a bit and learn their names from the start). Reinforce group rules for productive discussions---see Appendix E. If you ask someone to sit in and give feedback on your teaching, ask about course climate too.
7: To become self-directed learners, students must learn to assess the demands of the task, evaluate their own knowledge and skills, plan their approach, monitor their progress, and adjust their strategies as needed.
* p.192: I've never seen the point of concept maps, but the authors illustrate how they might help some learners in specific cases. Consider a student who just highlighted textbooks and memorized facts to get good grades in high school. Now, concept maps could help him transition if he's having trouble with college-level classes.
* p.194: Students with "a generic writing-as-knowledge-telling strategy ... presented everything that they knew about the paper's topic without regard to the specific goal or purpose of the assignment." (I admit I do this myself in early paper drafts, including my thesis proposal!) Again, you'll have to scaffold and hand-hold a bit, to help students transition from high-school expectations to college-level ones. Remind them to assess the task itself carefully.
* p.198: "...students who naturally monitor their own progress and try to explain to themselves what they are learning along the way generally show greater learning gains... Students who were taught or prompted to monitor their own understanding or to explain to themselves what they were learning had greater learning gains..." So, how can we teach students to self-monitor? I guess we can start by just prompting them often?
* p.207: You can scaffold a complex assignment by laying out a detailed plan with interim deadlines and deliverables... modeling the planning process for them... but after they have some experience, you can *also* ask them to make their own plan, so that this plan itself is a deliverable (and give them feedback on it).
* p.208: Teach students, or have them come up with, simple heuristics for self-checking. It should be possible to make a cheat-sheet of simple heuristics for Intro Stats; e.g., probabilities and variances should always be non-negative.
* p.209: Require students to do guided self-assessements: maybe they have to assess their own work against my rubric before submitting it for grading. Also ask them to reflect on and annotate their work process, e.g. in my Stat Graphics class they could keep a "process log" describing the iterations of their poster design and why they made certain design choices.
* p.211: Use "exam wrappers" (see also Appendix F). This is a short sheet to fill in when the exams are handed back, asking what mistakes they made; how they studied; and what they'll do differently to prepare better next time. Again, enforces reflection and planning.
* p.214: Model your own process for them, live. Show them how you assess the task, assess yourself, make a plan, monitor your own progress, reassess and readjust as you go, and evaluate final product. Especially for younger students, it helps to see that experts have to reassess too.
Appendices
* A: Self-assessments. Examples of multiple-choice questions for gauging a student's level of familiarity with a concept or tool.
* B: Concept maps. Again, I can't recall ever using these productively, but YMMV.
* C: Rubrics. Remember to include a category for "Mechanics" or similar (typos, proper citations, etc.), else it's not really fair to grade them.
* D: Learning objectives. Don't be too high-level; break down into its component skills: "problem solving may require defining the parameters of the problem, choosing appropriate formulas, and so on."
* E: Ground rules. If using these, establish them at start of the course, explain their purpose, get students' agreement, and hold students accountable. (Examples: Critique ideas, not people. Do not monopolize discussion. Use laptops only for legit class activities.) Also, step-by-step process for having students create their own ground rules---could be very useful for a discussion-heavy class.
* F: Exam wrappers. Example questions: How much time did you spend preparing? What percent of that time was spent on... (reading book for 1st time; reviewing homeworks; etc...)? What percent of points lost was for... (concept)? How will you prep next time?
* G: Checklists. (Could use rubrics for this? Attach to turned-in HW, checking off each part you did?)
* H: Peer review. Oddly specific instructions, but good Qs to reflect on & report.
December 10, 2019
This book is a part of a series from Jossy-Bass Higher and Adult Education series. I bought it on the recommendation of the learning resources center staff. They presented parts of the material during their new staff orientation.
I had two intentions, one was to have some resources at my disposal for the latest pedagogical theories to help my teaching and I also wanted to learn about these research based principles to help my coaching.
The structure of the book is straightforward, the introduction laid out the seven principles and stated their purpose: to bridge the research and teaching practices. The succeeding seven chapters laid out the seven principles, gave scenarios for the readers to digest and analyze. They discussed the theory and experimental results that supports each argument within the principles. The last section is a conclusion that reiterates the principles to close out the book. They have also included the eight tools that they have cited in the body of the book in the appendices to help the reader learn more about the implementation and pitfalls associated with these tools.
I found the presentations workmanlike, which is as intended. The idea is to present the principles cogently and logically, even though the topics that are covered are anything but coldly rational.
I was personally very interested in how students develop mastery and how they can become self-directed learners. Those two chapters drew me in when I first looked at the table of contents. As I read the book in the sequences presented by the author I was drawn into other principles, specifically, the chapters on how the student’s prior knowledge affected their learning and how they organized their knowledge made them look at the knowledge that they are accruing really made me think about those topics. I knew that those topics affect the students learning but I was not clever enough to see how teachers can incorporate tools to help the students deal with their lack of prior knowledge and how much the knowledge organization affect their learning process. Indeed, I started to think about my own learning process, and how ineffective some of my learning habits are, and yet I continue to persist in pursuing the same methods. I am changing my ways in response to that lesson.
The chapter on how the practice and the kind of feedback help the student to learn is enlightening because it gives me ideas on how to change my usual teaching tools to make the experience more productive for my students. The feedback topic is an important one and it is here that I received a lot of reassurance that the feedback skills that I have employed in my teaching and coaching are good practices and that my instincts were good ones. I did also profit from gaining more understanding of how feedback can be used.
The chapter on motivation and course climate were difficult ones for me, I took for granted that the motivation for the students are their responsibilities, that they were taking the class or playing on a team for a reason, that they were thusly motivated and I would have something to do with that, but not a lot. I am still a bit skeptical. I feel that motivation should be a personal decision, while I, as the teacher, can help them get more motivated by being a great teacher and being fair in my assessment of their abilities, I didn’t feel that I can make that much difference in how they are motivated. I am still dubious.
On the topic of the course climate, I can see where this chapter would be very useful and very pertinent in a social science class. I am in engineering so that we don’t have too much social discussions. I do see where the social climate of a class can make or break the classroom success of the students by how the class interacts socially and the kind of expectations that they the students and me the teacher would have due to the social constructs, societal norms and stereotypes that are realities in our society. Those issues really speak to the kind of person the teachers are and how their root beliefs guide them in their daily interaction with the students. Knowing that the effect on the students is an important part of opening the teacher’s eyes to the reality that they face but I m dubious about how they can transform their teaching according to this principle without completely changing their world view.
I will be referring back to this book often as I go forth in continuation of my teaching career. The principles are somewhat commonsensical, which makes it so much more acceptable. The no-nonsense layout of the arguments and methods are very welcome. The magical thing about the book is that it gives practical advice while also providing the readers with enough untethered hooks to hang onto intellectually so that they are challenged. This gives the readers some degrees of freedom to reflect on the ideas and allows them to progress the principles forward in their own ways.
I had two intentions, one was to have some resources at my disposal for the latest pedagogical theories to help my teaching and I also wanted to learn about these research based principles to help my coaching.
The structure of the book is straightforward, the introduction laid out the seven principles and stated their purpose: to bridge the research and teaching practices. The succeeding seven chapters laid out the seven principles, gave scenarios for the readers to digest and analyze. They discussed the theory and experimental results that supports each argument within the principles. The last section is a conclusion that reiterates the principles to close out the book. They have also included the eight tools that they have cited in the body of the book in the appendices to help the reader learn more about the implementation and pitfalls associated with these tools.
I found the presentations workmanlike, which is as intended. The idea is to present the principles cogently and logically, even though the topics that are covered are anything but coldly rational.
I was personally very interested in how students develop mastery and how they can become self-directed learners. Those two chapters drew me in when I first looked at the table of contents. As I read the book in the sequences presented by the author I was drawn into other principles, specifically, the chapters on how the student’s prior knowledge affected their learning and how they organized their knowledge made them look at the knowledge that they are accruing really made me think about those topics. I knew that those topics affect the students learning but I was not clever enough to see how teachers can incorporate tools to help the students deal with their lack of prior knowledge and how much the knowledge organization affect their learning process. Indeed, I started to think about my own learning process, and how ineffective some of my learning habits are, and yet I continue to persist in pursuing the same methods. I am changing my ways in response to that lesson.
The chapter on how the practice and the kind of feedback help the student to learn is enlightening because it gives me ideas on how to change my usual teaching tools to make the experience more productive for my students. The feedback topic is an important one and it is here that I received a lot of reassurance that the feedback skills that I have employed in my teaching and coaching are good practices and that my instincts were good ones. I did also profit from gaining more understanding of how feedback can be used.
The chapter on motivation and course climate were difficult ones for me, I took for granted that the motivation for the students are their responsibilities, that they were taking the class or playing on a team for a reason, that they were thusly motivated and I would have something to do with that, but not a lot. I am still a bit skeptical. I feel that motivation should be a personal decision, while I, as the teacher, can help them get more motivated by being a great teacher and being fair in my assessment of their abilities, I didn’t feel that I can make that much difference in how they are motivated. I am still dubious.
On the topic of the course climate, I can see where this chapter would be very useful and very pertinent in a social science class. I am in engineering so that we don’t have too much social discussions. I do see where the social climate of a class can make or break the classroom success of the students by how the class interacts socially and the kind of expectations that they the students and me the teacher would have due to the social constructs, societal norms and stereotypes that are realities in our society. Those issues really speak to the kind of person the teachers are and how their root beliefs guide them in their daily interaction with the students. Knowing that the effect on the students is an important part of opening the teacher’s eyes to the reality that they face but I m dubious about how they can transform their teaching according to this principle without completely changing their world view.
I will be referring back to this book often as I go forth in continuation of my teaching career. The principles are somewhat commonsensical, which makes it so much more acceptable. The no-nonsense layout of the arguments and methods are very welcome. The magical thing about the book is that it gives practical advice while also providing the readers with enough untethered hooks to hang onto intellectually so that they are challenged. This gives the readers some degrees of freedom to reflect on the ideas and allows them to progress the principles forward in their own ways.
December 4, 2023
So many tones that can be used to chant U.S.A U.S.A U.S.A
That said, notes.
1. Prior knowledge as strong foundation if robust, accurate and activated
a. Declarative vs procedural
b. Elaborative interrogation
c. Inappropriate priors: misconceptions, misapplications
d. Activate
i. Exercise to capture prior knowledge
ii. Link new material to previous
iii. Analogies to connect with knowledge/experience
iv. Use prior knowledge to reason / make predictions
2. Connections between pieces of knowledge to be meaningfully organized
a. Novices build sparse/superficial knowledge structures
b. Experts build rich meaningful structures
i. Hierarchy and Density of connections: chunking
ii. Advance organizer: set of principles providing cognitive structure
3. Motivation guides direction, intensity, persistency and quality of learning
a. Goals - Learning (achievement) vs performance (grades) vs Work-avoidant
b. Value - attainment, intrinsic (flow), instrumental (extrinsic)
i. Connect to student interests, authentic real-world tasks,
c. Expectancies: outcome (effort will pay off), efficacy (capable of pulling it off)
i. Align objectives, assessments, pedagogy. Levels of challenge. Early wins. Rubrics. Feedback. Study strategies.
4. Mastery through component skills that are combined, integrated and applied
a. Unconscious incompetence+knowledge->conscious competence + practice-> unconscious competence
5. Goal-directed practice with sufficient challenge, quantity, frequency with feedback
a. Goals will inform the practice. Leads to observed performance. Allows for targeted feedback shaped by goals. Guides further practice.
b. Feedback communicates status relative to goals. What to improve. Gives information when needed the most. Formative feedback (provides way forward) over summative feedback (evaluates proficiency)
6. Course has a social, emotional, intellectual climate that interacts with development
a. Chickering’s 7 vectors of student development: Competence (intellectual, physical - take control of own health and wellbeing, interpersonal). Manage emotions. Autonomy (emotional independence - break from parental approval - and instrumental independence - deal with issues). Identity. Mature interpersonal relationships. Purpose. Integrity (tension between self-interest and responsibility creates internally consistent set of values).
b. Intellectual development: from duality (right vs wrong) to multiplicity.
7. Self-directed learners can assess tasks, evaluate strengths, plan strategy
a. Assess task
i. Explicitly state task
ii. State what task is not
iii. Check student understanding
iv. Provide performance criteria
b. Evaluate strengths and weaknesses
i. Dunning Kruger
ii. Early performance based assessments - concept vs synthetic skill
iii. Opportunity for self-assessment
c. Plan strategy
i. Model plan - interim timelines and deliverables
ii. Planning as central goal of assignment
d. Apply strategy and monitor progress
i. Guided self-assessments
ii. Annotate your work
e. Adjust strategy
i. Reflective exercises
ii. Analyze effectiveness of study strategy
iii. Present multiple options
f. Beliefs about intelligence and learning
i. Broaden understanding of learning: declarative vs procedural vs contextual vs conceptual
That said, notes.
1. Prior knowledge as strong foundation if robust, accurate and activated
a. Declarative vs procedural
b. Elaborative interrogation
c. Inappropriate priors: misconceptions, misapplications
d. Activate
i. Exercise to capture prior knowledge
ii. Link new material to previous
iii. Analogies to connect with knowledge/experience
iv. Use prior knowledge to reason / make predictions
2. Connections between pieces of knowledge to be meaningfully organized
a. Novices build sparse/superficial knowledge structures
b. Experts build rich meaningful structures
i. Hierarchy and Density of connections: chunking
ii. Advance organizer: set of principles providing cognitive structure
3. Motivation guides direction, intensity, persistency and quality of learning
a. Goals - Learning (achievement) vs performance (grades) vs Work-avoidant
b. Value - attainment, intrinsic (flow), instrumental (extrinsic)
i. Connect to student interests, authentic real-world tasks,
c. Expectancies: outcome (effort will pay off), efficacy (capable of pulling it off)
i. Align objectives, assessments, pedagogy. Levels of challenge. Early wins. Rubrics. Feedback. Study strategies.
4. Mastery through component skills that are combined, integrated and applied
a. Unconscious incompetence+knowledge->conscious competence + practice-> unconscious competence
5. Goal-directed practice with sufficient challenge, quantity, frequency with feedback
a. Goals will inform the practice. Leads to observed performance. Allows for targeted feedback shaped by goals. Guides further practice.
b. Feedback communicates status relative to goals. What to improve. Gives information when needed the most. Formative feedback (provides way forward) over summative feedback (evaluates proficiency)
6. Course has a social, emotional, intellectual climate that interacts with development
a. Chickering’s 7 vectors of student development: Competence (intellectual, physical - take control of own health and wellbeing, interpersonal). Manage emotions. Autonomy (emotional independence - break from parental approval - and instrumental independence - deal with issues). Identity. Mature interpersonal relationships. Purpose. Integrity (tension between self-interest and responsibility creates internally consistent set of values).
b. Intellectual development: from duality (right vs wrong) to multiplicity.
7. Self-directed learners can assess tasks, evaluate strengths, plan strategy
a. Assess task
i. Explicitly state task
ii. State what task is not
iii. Check student understanding
iv. Provide performance criteria
b. Evaluate strengths and weaknesses
i. Dunning Kruger
ii. Early performance based assessments - concept vs synthetic skill
iii. Opportunity for self-assessment
c. Plan strategy
i. Model plan - interim timelines and deliverables
ii. Planning as central goal of assignment
d. Apply strategy and monitor progress
i. Guided self-assessments
ii. Annotate your work
e. Adjust strategy
i. Reflective exercises
ii. Analyze effectiveness of study strategy
iii. Present multiple options
f. Beliefs about intelligence and learning
i. Broaden understanding of learning: declarative vs procedural vs contextual vs conceptual
October 14, 2019
I really wish there were more books written like How Learning Works, not just on education but on academic research in general. The title sounds a bit like it could be one of a zillion popular science books, but it's far from that - rather, it is a collation and exposition of a wide body of research literature on teaching and learning, organized into seven major principles, and completed with a comprehensive list of applications and strategies based on those principles. It is written with the non-expert in mind (in particular, the target audience is college professors who likely have not had significant formal training in teaching and pedagogy), so the authors assume no background in the literature and stay away from heavy use of jargon. At the same time, they dive deep and provide a lot of evidence for the practices they suggest, doing a great job of explaining complex pedagogical concepts clearly.
I would have liked to see a little bit more content on educational psychology/neuroscience and how that plays into the seven principles - I feel that understanding how our brains operate when learning can be really helpful when it comes to thinking about teaching methods and strategies. Also, some of the points the authors raised felt fairly common-sense, although what may seem like common sense to me might be totally mind-blowing for someone else, and it's always good to put solid research behind your common-sense ideas as well.
I'm sure the book barely puts a dent in the massive body of research on education out there, but it already contains way too much material to really process and apply after a single reading. This is definitely a book to come back to and read more slowly (slower than I already was reading this book haha) and deliberately. I'm honestly thinking a chapter per semester will give me enough time to digest the material and get some practice with the strategies without getting overwhelmed.
I would have liked to see a little bit more content on educational psychology/neuroscience and how that plays into the seven principles - I feel that understanding how our brains operate when learning can be really helpful when it comes to thinking about teaching methods and strategies. Also, some of the points the authors raised felt fairly common-sense, although what may seem like common sense to me might be totally mind-blowing for someone else, and it's always good to put solid research behind your common-sense ideas as well.
I'm sure the book barely puts a dent in the massive body of research on education out there, but it already contains way too much material to really process and apply after a single reading. This is definitely a book to come back to and read more slowly (slower than I already was reading this book haha) and deliberately. I'm honestly thinking a chapter per semester will give me enough time to digest the material and get some practice with the strategies without getting overwhelmed.
February 24, 2024
🎓 Insegnare è un’arte? Docenti capaci si nasce o si diventa? 🤔
Sono sicuro che, se nel tuo percorso professionale hai provato almeno una volta a insegnare qualcosa, questo argomento ti interessa📚
Di recente ho letto "Come impariamo. Sette principi per un insegnamento efficace", un libro basato su scienze cognitive e sperimentazioni nelle aule delle università americane. La tesi del libro è affascinante: docenti capaci si può diventare e se ci si nasce, si può sempre migliorare🚀
Ecco cinque spunti chiave dal libro che ritengo utili per chi si occupa di formazione aziendale e non solo:
1️⃣ Le conoscenze pregresse di chi partecipa alla formazione influenzano l'apprendimento. Chi trovi in aula non è una tabula rasa, ma porta con sé un bagaglio di esperienze e conoscenze. È come un puzzle, e noi siamo qui per aiutare a trovare i pezzi giusti.
2️⃣ L'organizzazione delle conoscenze è essenziale. Immagina di spiegare un concetto complesso e vedere come risposta uno sguardo spaesato. Forse è il momento di adottare un approccio per aiutare chi apprende a creare nuove connessioni.
3️⃣ La motivazione è la chiave. Come sappiamo bene, se le persone non vedono il valore per i loro obiettivi in ciò che insegniamo, rischiamo di perdere il loro interesse. Proviamo a rendere ogni lezione come una sfida da vincere.
4️⃣ L'atmosfera dell'aula è cruciale. Non ci occupiamo solo di educazione (di persone adulte), ma creiamo delle esperienze. L'ambiente in cui apprendiamo può fare la differenza tra l'entusiasmo e la noia.
5️⃣ Imparare a valutare è essenziale per un apprendimento duraturo. Aiutiamo chi partecipa al corso a valutare le sue competenze e a regolare il proprio percorso di apprendimento, proprio come chi si prepara a una corsa di fondo si allena per migliorare costantemente.
Sono sicuro che, se nel tuo percorso professionale hai provato almeno una volta a insegnare qualcosa, questo argomento ti interessa📚
Di recente ho letto "Come impariamo. Sette principi per un insegnamento efficace", un libro basato su scienze cognitive e sperimentazioni nelle aule delle università americane. La tesi del libro è affascinante: docenti capaci si può diventare e se ci si nasce, si può sempre migliorare🚀
Ecco cinque spunti chiave dal libro che ritengo utili per chi si occupa di formazione aziendale e non solo:
1️⃣ Le conoscenze pregresse di chi partecipa alla formazione influenzano l'apprendimento. Chi trovi in aula non è una tabula rasa, ma porta con sé un bagaglio di esperienze e conoscenze. È come un puzzle, e noi siamo qui per aiutare a trovare i pezzi giusti.
2️⃣ L'organizzazione delle conoscenze è essenziale. Immagina di spiegare un concetto complesso e vedere come risposta uno sguardo spaesato. Forse è il momento di adottare un approccio per aiutare chi apprende a creare nuove connessioni.
3️⃣ La motivazione è la chiave. Come sappiamo bene, se le persone non vedono il valore per i loro obiettivi in ciò che insegniamo, rischiamo di perdere il loro interesse. Proviamo a rendere ogni lezione come una sfida da vincere.
4️⃣ L'atmosfera dell'aula è cruciale. Non ci occupiamo solo di educazione (di persone adulte), ma creiamo delle esperienze. L'ambiente in cui apprendiamo può fare la differenza tra l'entusiasmo e la noia.
5️⃣ Imparare a valutare è essenziale per un apprendimento duraturo. Aiutiamo chi partecipa al corso a valutare le sue competenze e a regolare il proprio percorso di apprendimento, proprio come chi si prepara a una corsa di fondo si allena per migliorare costantemente.
April 6, 2020
I come to this book to learn for myself first, then for my students.
It’s hard to understand why we are not taught how to learn at first. After graduation, I heard about metacognition for the first time. And that’s the first time I know the power and meaning of education, the first time I know what I had been doing wrong for 17 years of education. I don’t know why students don’t learn about how powerful their brains are and how they works. That’s why most of my friends as well as students believe that we are only good at subjects we are born for, the rest is not for us, no need to learn them.
Now I’m trying to complete the missing pieces in my knowledge, and use them to teach my students. The book provides 7 principles for teaching developed from how students learn. It will take time to practice those principles but it’s worth it. I hope to see lots of improvement in my class.
Interestingly, I can apply what I learn from the book right now on anything I do in life, because I know what a self-direct learner looks like.
It’s hard to understand why we are not taught how to learn at first. After graduation, I heard about metacognition for the first time. And that’s the first time I know the power and meaning of education, the first time I know what I had been doing wrong for 17 years of education. I don’t know why students don’t learn about how powerful their brains are and how they works. That’s why most of my friends as well as students believe that we are only good at subjects we are born for, the rest is not for us, no need to learn them.
Now I’m trying to complete the missing pieces in my knowledge, and use them to teach my students. The book provides 7 principles for teaching developed from how students learn. It will take time to practice those principles but it’s worth it. I hope to see lots of improvement in my class.
Interestingly, I can apply what I learn from the book right now on anything I do in life, because I know what a self-direct learner looks like.
November 27, 2018
I actually really liked this one! The authors are clear communicators, topics and concepts are laid out in an organized way, and actionable steps are understandable. As someone who very much appreciates the practical and tangible aspects, in tandem with the philosophical and theoretical ways of thinking, of learning and teaching, this book was perfect. It is easy to ignore the suggestions that are already intuitive to me, while gleaning so much from all the tips that are new to me or at least unnatural. I found myself starring the strategies I hoped to integrate into my own teaching for continual reference. I appreciated the specific examples given in each chapter, the explanation of aspects of learning, the tangible strategies, and the logical progression of the order topics were presented. This book transformed my own learning and teaching processes.
April 6, 2020
This is a really good book for teachers, as the authors do a nice job integrating academic research with practical classroom concerns. They don't get lost in the weeds of t-tests and sample size, but neither is the advice simply platitudinous. The first four chapters, on prior knowledge, knowledge organization, motivation and the development of mastery, are particularly good. Chapters 5 and 6 on practice and feedback and classroom culture and student development felt like a bit of a letdown, without much new to say. I think that's because there wasn't much revelatory in the research on classroom culture, or on the practical side of practice and feedback. In general, I find good teaching books to be ones that remind me of best practices, give me new examples of those practices at work, and frame some familiar ideas in new ways, and (most of) this book definitely delivered.
March 20, 2018
I love the book. Being a novice teacher for one year, I often find myself overwhelmed and lost into which practices work best for my students. The book provides concrete and research based principles for teaching with detailed explanations and specific examples, which makes it so much easier to understand. The book also gives direct advices on what to do, how and when to do it so as to achieve the most effective results. What I find particularly inspiring is the last chapter where all 7 principles of learning for students are applied on instructors ourselves as we are learning to teach ourselves. I find this chapter highly relatable and personally touching. A big thank to all the authors of the book <3
October 27, 2019
This book reviews seven principles of effective teaching: prior knowledge, organization, motivation, how to develop mastery, practice, course climate, and self-directed learners. All of the principles are well grounded by research. It's geared to college but has broader applications. Each chapter begins with two fictional challenges (based on real ones) faced by teachers. These are really good. They all ring true and are a great insight into how one's perspective of a problem is very important. Each chapter is laced with examples from a broad range of subjects. The ideas in this book are valuable, but they're the first step. Each teacher will need to put in a lot of time to implement them for their subject and students.
Read
January 1, 2016Do - misconceptions tend to be shared and produce consistent patterns => find MOOC data for specific subject content areas
Negative reinforcement doesn't mean punishment. It means removing something adverse to increase a desired behavior.
How can technology combat global poverty?
Understand what to do and why. "Is this a reasonable answer?" "What assumptions am I making here?"
Reflect, is the current approach working? "Is this strategy working?"
p 13 If that knowledge is inactive--it may not facilitate the integration of new knowledge. [d/dx(cos^-1(...)]
p 31 Once activated relevant prior knowledge, you're likely able to integrate new knowledge better.
p 16 Asking explicit questions to specifically trigger recall helps use prior knowledge:
> "Think back to..."
> "Where have I seen [this] before?"
p 62 explicitly connect it to what else you have learned, where those connects don't have to be similarities; find contrast and discrepancies.
p 20 Studies in statistics, show how commonplace definitions intrude in technical contests.
[extreme vs relative poverty]
p 21 composition courses ~ teaching a generic approach to writing (not domain specific)
p 24 misconceptions are deeply embedded
p 25 misconceptions often include accurate--as well as inaccurate--elements.
p 26 stereotypical judgments <~ misconceptions require more cognitive energy, i.e., bridging:
table exerts F on a book, somewhat counter-intuitive, compressed spring analogy--the intermediate serves to bridge the difference between
p 27 usually unlikely to be enough for inaccuracies to be corrected by being exposed to accurate info
p 30 concept map, unless everything, specify particular kinds of info (causal relationships, examples, theoretical orientations)
p 43 experts organize knowledge around meaningful features and abstract principles; interconnected (and causal) enabling the ability to reason, which is a more robust foundation for subsequent learning.
p 56 Grandmasters can glance at a particular game, take and empty board, and replicate the exact positions. This isn't a result of superior memory, but a reflection of the deep and intricate set of relationships they can see among pieces that they automatically use during play. (Organizing knowledge around meaningful features and patterns.)
p 63 categorize them according to more than one organizational schema; first on...and then on the basis of...
p 48 The usefulness of knowledge organizations depends on the tasks they need to support.
p 53 When students are provided with an organizational structure to fit new knowledge, they learn more effectively. [Why?!]
p 58 problems that are already solved, explain the solution; explain why the solution is the way it is--how?
p 71 pursue learning for its own sake (where most students are motivated primarily by performance goals)
p 72 When guided by learning goals, students try to gain competence and truly learn what an activity or task can teach them.
p 76 challenging problems ~ attainment value
p 75 instrumental value [employers looking at grades] AKA extrinsic rewards vs intrinsic value/motivation
p 73 students who hold multiple types of goals are more successful
p 103 cognitive load - when your limit is exceeded, insufficient attention (and other cognitive resources) [=> lower than average: ADD?]
p 105 focus on one skill at a time (not concurrently), reducing your cognitive load, giving yourself the opportunity to develop fluency; first learn A, then use A with B. [Don't hit two birds, but*]
p 106 *removing extraneous load--aspects unrelated to what's needed to learn--making it harder is helpful: extraneous vs germane load.
p 116 piano, practice only the right hand part of the piece, and then only the left
http://www.simulations.co.uk/images/C...
p 108 transfer means applying skills learned on one context to a novel context.
p 110 opportunities to do applications in multiple contexts (allows less context-dependent, more 'flexible' knowledge)
p 119 "what if" questions [THROW A WRENCH IN IT!]
p 163 In the earlier stages, reasoning is a basic duality where knowledge is divided into right and wrong. At this stage of intellectual development, people believe that knowledge is something absolute. For example, education is a process of amassing piles of 'right' facts.
p 164 Students move forward to a stage of multiplicity. Knowledge, anyone can have an opinion. Then, we progress to stages characterized by relativism. Here we realize, as a worldview, that opinions are not all equal.
p 181 Encourage group participation by validating different viewpoints, even unpopular ones.
p 185 Address tensions early, address the issue before it gets out of hand.
p 214 YouTube instructors may model metacognition out load
Vocab
concept inventories - list of concepts
declarative knowledge - knowing what and why
procedural knowledge - knowing how and when
temporal contiguity (p 46)
efficacy - ability to produce a desired/intended result
germane -
scaffolding - worked example effect - presolved problems (example of scaffolding)
scaffolding - cognitive supports, then gradually remove
far transfer - central goal of education, applying what you've learned beyond academia
overspecificity or context dependence - associating knowledge too closely with the context originally learned
exam wrapper -
1. What errors did you think you made?
2. How did you study?
3. What will you do differently?
Negative reinforcement doesn't mean punishment. It means removing something adverse to increase a desired behavior.
How can technology combat global poverty?
Understand what to do and why. "Is this a reasonable answer?" "What assumptions am I making here?"
Reflect, is the current approach working? "Is this strategy working?"
p 13 If that knowledge is inactive--it may not facilitate the integration of new knowledge. [d/dx(cos^-1(...)]
p 31 Once activated relevant prior knowledge, you're likely able to integrate new knowledge better.
p 16 Asking explicit questions to specifically trigger recall helps use prior knowledge:
> "Think back to..."
> "Where have I seen [this] before?"
p 62 explicitly connect it to what else you have learned, where those connects don't have to be similarities; find contrast and discrepancies.
p 20 Studies in statistics, show how commonplace definitions intrude in technical contests.
[extreme vs relative poverty]
p 21 composition courses ~ teaching a generic approach to writing (not domain specific)
p 24 misconceptions are deeply embedded
p 25 misconceptions often include accurate--as well as inaccurate--elements.
p 26 stereotypical judgments <~ misconceptions require more cognitive energy, i.e., bridging:
table exerts F on a book, somewhat counter-intuitive, compressed spring analogy--the intermediate serves to bridge the difference between
p 27 usually unlikely to be enough for inaccuracies to be corrected by being exposed to accurate info
p 30 concept map, unless everything, specify particular kinds of info (causal relationships, examples, theoretical orientations)
p 43 experts organize knowledge around meaningful features and abstract principles; interconnected (and causal) enabling the ability to reason, which is a more robust foundation for subsequent learning.
p 56 Grandmasters can glance at a particular game, take and empty board, and replicate the exact positions. This isn't a result of superior memory, but a reflection of the deep and intricate set of relationships they can see among pieces that they automatically use during play. (Organizing knowledge around meaningful features and patterns.)
p 63 categorize them according to more than one organizational schema; first on...and then on the basis of...
p 48 The usefulness of knowledge organizations depends on the tasks they need to support.
p 53 When students are provided with an organizational structure to fit new knowledge, they learn more effectively. [Why?!]
p 58 problems that are already solved, explain the solution; explain why the solution is the way it is--how?
p 71 pursue learning for its own sake (where most students are motivated primarily by performance goals)
p 72 When guided by learning goals, students try to gain competence and truly learn what an activity or task can teach them.
p 76 challenging problems ~ attainment value
p 75 instrumental value [employers looking at grades] AKA extrinsic rewards vs intrinsic value/motivation
p 73 students who hold multiple types of goals are more successful
p 103 cognitive load - when your limit is exceeded, insufficient attention (and other cognitive resources) [=> lower than average: ADD?]
p 105 focus on one skill at a time (not concurrently), reducing your cognitive load, giving yourself the opportunity to develop fluency; first learn A, then use A with B. [Don't hit two birds, but*]
p 106 *removing extraneous load--aspects unrelated to what's needed to learn--making it harder is helpful: extraneous vs germane load.
p 116 piano, practice only the right hand part of the piece, and then only the left
http://www.simulations.co.uk/images/C...
p 108 transfer means applying skills learned on one context to a novel context.
p 110 opportunities to do applications in multiple contexts (allows less context-dependent, more 'flexible' knowledge)
p 119 "what if" questions [THROW A WRENCH IN IT!]
p 163 In the earlier stages, reasoning is a basic duality where knowledge is divided into right and wrong. At this stage of intellectual development, people believe that knowledge is something absolute. For example, education is a process of amassing piles of 'right' facts.
p 164 Students move forward to a stage of multiplicity. Knowledge, anyone can have an opinion. Then, we progress to stages characterized by relativism. Here we realize, as a worldview, that opinions are not all equal.
p 181 Encourage group participation by validating different viewpoints, even unpopular ones.
p 185 Address tensions early, address the issue before it gets out of hand.
p 214 YouTube instructors may model metacognition out load
Vocab
concept inventories - list of concepts
declarative knowledge - knowing what and why
procedural knowledge - knowing how and when
temporal contiguity (p 46)
efficacy - ability to produce a desired/intended result
germane -
scaffolding - worked example effect - presolved problems (example of scaffolding)
scaffolding - cognitive supports, then gradually remove
far transfer - central goal of education, applying what you've learned beyond academia
overspecificity or context dependence - associating knowledge too closely with the context originally learned
exam wrapper -
1. What errors did you think you made?
2. How did you study?
3. What will you do differently?
Displaying 1 - 30 of 130 reviews