The learning-science library
These are the 100+ papers DuckyHelper's tutor is built on: tutoring, retrieval practice, spacing, worked examples, feedback, pictures and words, AI tutors and more. Each entry gives the real title, authors, year and journal, a link to the publisher or DOI, our one-line summary, and where we checked it, a short quote in the paper's own words. Browse by principle or topic.
How we checked every entry
- Every paper is real: its title, authors, year and journal were matched against Crossref or OpenAlex, and we hold the full text of 129 of them.
- A quote is only shown when we found it word for word: in the paper's PDF (103 papers), in a scanned PDF read with text recognition (5), or in the published abstract (11). One quote we could not check against the article is left out.
- The one-line summary under each title is ours, in plain words. It is never shown as a quote.
- We link to the publisher, the DOI or the authors' own page. We do not host copies of the papers.
Download the annotated bibliography (PDF): every paper in the library with its full citation and our note.
Browse the papers
Pick a principle or a topic, or search by title, author, year or journal. Each title links to the publisher or the DOI.
146 papers
The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring
Tutored students scored about two standard deviations above students taught in class.
“the average student under tutoring was about two standard deviations above the average of the control class”
Learning from human tutoring
Students learned just as well when tutors prompted instead of explaining.
“students learned just as effectively even when tutors were suppressed from giving explanations and feedback”
The Wisdom of Practice: Lessons Learned from the Study of Highly Effective Tutors
The best math tutors tend motivation and emotion, not just cognition.
The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems
Step-based tutoring systems came nearly as close as human tutors.
“the effect size of intelligent tutoring systems was 0.76, so they are nearly as effective as human tutoring”
The Promise of Tutoring for PreK-12 Learning: A Systematic Review and Meta-Analysis of the Experimental Evidence
Tutoring programs show consistent, substantial gains, about 0.29 standard deviations.
“tutoring programs yield consistently substantial positive impacts on learning”
Generative AI without guardrails can harm learning: Evidence from high school mathematics
Unguarded GPT-4 help lifted practice grades, then cut exam grades 17%.
“unfettered access to GPT-4 can harm educational outcomes”
Test-Enhanced Learning: Taking Memory Tests Improves Long-Term Retention
Taking recall tests beat restudying for remembering material days later.
“Testing is a powerful means of improving learning, not just assessing it.”
The Critical Importance of Retrieval for Learning
Repeated testing, not repeated studying, drove long-term vocabulary recall.
“Repeated studying after learning had no effect on delayed recall, but repeated testing produced a large positive effect”
Retrieval Practice Produces More Learning than Elaborative Studying with Concept Mapping
Practicing recall beat concept mapping, even on a concept-mapping test.
“practicing retrieval produces greater gains in meaningful learning than elaborative studying with concept mapping”
Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology
Of ten study techniques, practice testing and spacing were rated most useful.
“Practice testing and distributed practice received high utility assessments”
Über das Gedächtnis: Untersuchungen zur experimentellen Psychologie
First experiments on memory, charting the forgetting curve and effects of repetition.
Distributed practice in verbal recall tasks: A review and quantitative synthesis
Across 317 experiments, spacing helps, and longer retention calls for longer gaps.
“the ISI producing maximal retention increased as retention interval increased”
Organizing Instruction and Study to Improve Student Learning
Seven research-based recommendations, including spacing, worked examples and quizzing.
The Use of Worked Examples as a Substitute for Problem Solving in Learning Algebra
Studying worked examples beat problem solving for novices: faster, with fewer errors.
“worked examples, as expected, require considerably less time to process than conventional problems”
Cognitive Load During Problem Solving: Effects on Learning
Conventional problem solving eats working memory needed to learn the underlying schemas.
“conventional problem‐solving activity is not effective in schema acquisition”
Learning from Examples: Instructional Principles from the Worked Examples Research
Good worked examples are integrated and placed right next to matched practice.
“examples should be presented in close proximity to matched practice problems”
Toward an Instructionally Oriented Theory of Example-Based Learning
Examples are a very effective way to start learning a new skill.
“Learning from examples is a very effective means of initial cognitive skill acquisition”
The Role of Tutoring in Problem Solving
Good tutors handle what is beyond the learner and leave the rest to them.
Mind in Society: The Development of Higher Psychological Processes
Learners can do more with guidance than alone: the zone of proximal development.
“the distance between the actual developmental level as determined by independent problem solving”
The Expertise Reversal Effect
Techniques that help novices can backfire with more experienced learners.
“Instructional techniques that are highly effective with inexperienced learners can lose their effectiveness”
Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching
For novices, minimal guidance is less effective than strong, explicit guidance.
“minimally guided instruction is less effective and less efficient than instructional approaches that place a strong emphasis on guidance”
Scaffolding vs. Hints in the Assistment System
Compares breaking a missed problem into scaffolding questions against giving hints on request in ASSISTments.
Experimental Evaluation of Automatic Hint Generation for a Logic Tutor
Hints generated automatically from past students' data helped students persist in a logic course.
“hints help students persist in deductive logic courses”
Principles of Instruction: Research-Based Strategies That All Teachers Should Know
Ten research-based principles, like small steps and checking every student's understanding.
“Present new material in small steps with student practice after each step”
Why a Diagram is (Sometimes) Worth Ten Thousand Words
Diagrams can make problem solving easier because they put related information in one place.
“Diagrammatic representations are indexed by location in a plane”
Dual coding theory and education
Memory has verbal and imagery codes, and teaching can use both.
Animation: can it facilitate?
A review that asks whether animation beats static graphics, and finds the benefits often come from other differences.
“The assumption is that graphics can facilitate comprehension, learning, memory, communication and inference”
Nine Ways to Reduce Cognitive Load in Multimedia Learning
People learn by linking pictures and words, if neither channel is overloaded.
“meaningful learning involves cognitive processing including building connections between pictorial and verbal representations”
Activity and Imagined Activity Can Enhance Young Children's Reading Comprehension
Young readers who moved toys (or imagined moving them) to act out a story understood and remembered it better.
“Both actual manipulation and imagined manipulation resulted in markedly better (compared with rereading) memory for and comprehension of the text material”
The Promise and Practice of Learner-Generated Drawing: Literature Review and Synthesis
A review of research on students making their own drawings to learn.
DeFT: A conceptual framework for considering learning with multiple representations
The DeFT framework for when learning with several representations (text, graphs, pictures) helps.
“Multiple (external) representations can provide unique benefits when people are learning complex new ideas”
Gesturing makes learning last
Children who gestured while learning a new math idea kept what they learned better.
“requiring children to gesture while learning the new concept helped them retain the knowledge they had gained during instruction”
Gesturing Gives Children New Ideas About Math
Children told to make correct gestures during a math lesson learned more than children making partial or no gestures.
“children required to produce correct gestures learned more than children required to produce partially correct gestures, who learned more than children required to produce no gestures”
Drawing to Learn in Science
Argues that drawing should be a key part of science education.
“Emerging research suggests drawing should be explicitly recognized as a key element in science education”
The Cognitive Science of Visual-Spatial Displays: Implications for Design
A review of the cognitive science of graphs, maps and diagrams, and what it means for designing them.
“This paper reviews cognitive science perspectives on the design of visual-spatial displays”
Gesture's Role in Speaking, Learning, and Creating Language
A review of how gesture helps people speak, think and learn.
“the gestures speakers produce when they talk are integral to communication”
Drawing pictures during learning from scientific text: testing the generative drawing effect and the prognostic drawing effect
Tests whether drawing pictures while reading a science text improves learning, and whether drawing quality predicts it.
Creating visual explanations improves learning
Students who created visual explanations of a bicycle pump and of chemical bonding learned more.
“creating a visual explanation increased understanding particularly for participants of low spatial ability”
Effects of observing the instructor draw diagrams on learning from multimedia messages
Watching an instructor draw diagrams while explaining helped low prior knowledge learners transfer more than seeing finished diagrams.
“watching the instructor draw diagrams (by viewing the instructor's full body) resulted in significantly better transfer test performance than viewing already-drawn diagrams for learners with low prior knowledge”
The drawing effect: Evidence for reliable and robust memory benefits in free recall
Drawing a word's meaning made it easier to recall than writing the word out, across seven experiments.
“Drawn words were better recalled than written”
Formative assessment and the design of instructional systems
A theory of formative assessment: learners need to know the goal, where they are, and how to close the gap.
“Feedback is defined in a particular way to highlight its function in formative assessment”
The Instructional Effect of Feedback in Test-like Events
A meta-analysis of 58 effect sizes on feedback after test-like questions.
“The present meta-analysis reviewed 58 effect sizes from 40 reports”
Cognitive Tutors: Lessons Learned
Tutors giving immediate feedback matched classroom results in a third of the time.
“the tutor provides immediate feedback, consisting of short and directed error messages”
Feedback and Self-Regulated Learning: A Theoretical Synthesis
A theory of how feedback works inside self-regulated learning, including the feedback learners give themselves.
The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory
Feedback helps on average, but over a third of interventions hurt performance.
“FI effectiveness decreases as attention moves up the hierarchy closer to the self and away from the task”
Assessment and Classroom Learning
A landmark review of classroom formative assessment and the learning gains from frequent feedback.
“innovations designed to strengthen the frequent feedback that students receive about their learning yield substantial learning gains”
Help Seeking and Help Design in Interactive Learning Environments
A review of on-demand help in learning software: learners often do not use help well.
“learners are not using help facilities effectively”
Off-Task Behavior in the Cognitive Tutor Classroom: When Students "Game the System"
Students who abused hints and feedback to get answers learned much less than students who did not.
“students who frequently game the system score substantially lower on a post-test than students who never game the system”
Toward Meta-cognitive Tutoring: A Model of Help Seeking with a Cognitive Tutor
Extends the Cognitive Tutor with a model of good and bad help seeking so it can coach how students ask for help.
“an intelligent tutoring system that provides guidance with respect to students' meta-cognitive abilities can help them to become better learners”
Formative assessment and self-regulated learning: a model and seven principles of good feedback practice
Seven principles of good feedback practice that help students take control of their own learning.
“seven principles of good feedback practice that support self-regulation”
The Power of Feedback
Feedback strongly shapes learning, but its type and delivery decide the effect.
“Feedback is one of the most powerful influences on learning and achievement”
Focus on Formative Feedback
Formative feedback works best when supportive, timely and specific.
“formative feedback should be nonevaluative, supportive, timely, and specific”
Improving students’ help-seeking skills using metacognitive feedback in an intelligent tutoring system
The Help Tutor gave students immediate feedback on how they used hints in a geometry tutor.
“The present research investigated whether immediate metacognitive feedback on students' help-seeking errors can help students acquire better help-seeking skills”
The Power of Feedback Revisited: A Meta-Analysis of Educational Feedback Research
A meta-analysis of 435 studies on feedback; effects vary a lot with what information the feedback carries.
“Overall results based on a random-effects model indicate a medium effect (d = 0.48) of feedback on student learning”
Self-Explanations: How Students Study and Use Examples in Learning to Solve Problems
Students who explain worked examples to themselves learn with real understanding.
““Good” students learn with understanding: They generate many explanations”
Eliciting Self-Explanations Improves Understanding
Prompting eighth graders to self-explain deepened their understanding of circulation.
“Generating explanations to oneself (self‐explaining) facilitates that integration process”
Memory and Metamemory Considerations in the Training of Human Beings
Conditions that make practice harder can make learning last longer.
The shuffling of mathematics problems improves learning
Mixing different problem types in practice improved later math test scores.
Learning Concepts and Categories: Is Spacing the “Enemy of Induction”?
Interleaving artists' paintings improved learning each style, though massing felt better.
“Surprisingly, induction profited from spacing, even though massing apparently created a sense of fluent learning”
The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues
Compares Blender and GPT-3 replies with real teachers' replies in the same dialogues on speaking like a teacher, understanding a student and helping a student.
“speak like a teacher, understand a student, help a student”
MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems
LLMs solve math well but reveal solutions too early when tutoring.
“While models like GPT-3 are good problem solvers, they fail at tutoring”
Opportunities and Challenges in Neural Dialog Tutoring
Tests generative language models on two language-learning tutoring datasets and maps where they still fall short of human tutors.
“dialog tutoring has largely remained unaffected by these advances”
Language Models as Science Tutors
TutorEval tests whether language models can answer questions about long textbook chapters the way a science tutor would, and TutorChat trains for it.
“fine-tuning base models with existing dialogue datasets leads to poor performance on TutorEval”
Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model Tutors
A dataset of student math solutions with the first wrong step marked by teachers; tutors that first find the error give better feedback.
“they struggle to precisely detect student's errors and tailor their feedback to these errors”
Effective and Scalable Math Support: Experimental Evidence on the Impact of an AI-Math Tutor in Ghana
A field experiment with about 500 students in Ghana using Rori, a WhatsApp math tutor, one hour a week during study hall.
“an AI-powered math tutor accessible via WhatsApp”
Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach
Educators and learners preferred a pedagogy-tuned Gemini tutor over prompting alone.
“LearnLM-Tutor is consistently preferred over a prompt tuned Gemini by educators and learners”
LearnLM: Improving Gemini for Learning
Training on teaching instructions made Gemini the experts' pick for learning.
“tuned to present information by default, rather than engage users in service of learning”
SocraticLM: Exploring Socratic Personalized Teaching with Large Language Models
An LLM tuned on Socratic teaching dialogues out-taught GPT-4.
“actively engaging students in the thought process required for genuine problem-solving mastery”
ChatGPT-generated help produces learning gains equivalent to human tutor-authored help on mathematics skills
ChatGPT-written hints produced learning gains comparable to human tutor hints.
“only the ChatGPT condition produces statistically significant learning gains compared to a no-help control”
Ruffle&Riley: Insights from Designing and Evaluating a Large Language Model-Based Conversational Tutoring System
A conversational tutor where two LLM agents, a student and a professor, let the learner teach and be taught from a lesson text.
“orchestration in a learning-by-teaching format via two LLM-based agents”
Pedagogical Alignment of Large Language Models
Trains LLMs with preference learning to guide students through problems rather than reply with the answer at once.
“often provide immediate answers rather than guiding students through the problemsolving process”
Bridging the Novice-Expert Gap via Models of Decision-Making: A Case Study on Remediating Math Mistakes
Adding expert remediation decisions made LLM tutor replies far more preferred.
“the expert's decision-making model is critical for LLMs to close the gap”
Tutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise
AI guidance for human tutors raised student topic mastery by 4 points.
“less likely to give away the answer to the student”
From Chalkboards to Chatbots: Evaluating the Impact of Generative AI on Learning Outcomes in Nigeria
A randomized trial in Nigeria where secondary students used Microsoft Copilot (GPT-4) for English as an after-school tutor for six weeks.
“The effect on English, the main outcome of interest, was of 0.23 standard deviations”
From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement Learning
Uses reinforcement learning with simulated students to turn an LLM into a tutor that guides instead of giving away answers.
“effective pedagogy which requires strategically withholding answers”
AI tutoring outperforms in-class active learning: an RCT introducing a novel research-based design in an authentic educational setting
Students learned more in less time with an AI tutor than in class.
“students learn significantly more in less time when using the AI tutor”
Evaluating Gemini in an arena for learning
Educators ran blind, head-to-head tutoring comparisons of leading AI models.
“experts preferred Gemini 2.5 Pro in 73.2% of these match-ups”
MathTutorBench: A Benchmark for Measuring Open-ended Pedagogical Capabilities of LLM Tutors
An open benchmark for how well LLMs teach math, with a reward model that tells expert from novice tutor replies; solving skill did not translate into good teaching.
“subject expertise, indicated by solving ability, does not immediately translate to good teaching”
Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors
An eight-dimension benchmark for judging how well LLMs actually tutor.
“highlighting which LLMs are good tutors and which ones are more suitable as question-answering systems”
Training LLM-Based Tutors to Improve Student Learning Outcomes in Dialogues
Trains an LLM tutor to pick replies that a model predicts will help the student answer correctly, while keeping the replies pedagogically sound.
“they are not trained to maximize student learning throughout the course of a dialogue”
- How tutors talk
Collaborative dialogue patterns in naturalistic one-to-one tutoring
Everyday tutoring works through joint problem solving, questions and explanation with examples.
“Naturalistic one‐to‐one tutoring is more effective than traditional classroom teaching methods”
- How tutors talk
Understanding Tutor Learning: Knowledge-Building and Knowledge-Telling in Peer Tutors’ Explanations and Questions
Peer tutors mostly tell knowledge instead of building it with students.
“Peer tutors, even when trained, focus more on delivering knowledge rather than developing it”
- How tutors talk
Deliberative Discourse Idealized and Realized: Accountable Talk in the Classroom and in Civic Life
Describes Accountable Talk, classroom discussion practices that hold students to reasoning, evidence and each other's ideas.
“Classroom discussion practices that can lead to reasoned participation by all students are presented and described by the authors”
- How tutors talk
Dialogue Act Modeling in a Complex Task-Oriented Domain
A classifier for dialogue acts in computer-programming tutoring that uses both the chat and the student's task actions.
“The task-oriented domain involves tutoring in computer programming exercises”
- How tutors talk
The Teacher-Student Chatroom Corpus
A corpus of one-to-one online chat lessons between English teachers and learners, with scaffolding and correction annotated.
“the teacher was able to focus exclusively on the linguistic abilities and errors of the student”
- How tutors talk
CIMA: A Large Open Access Dialogue Dataset for Tutoring
A tutoring dialogue dataset where tutors choose between hints and questions.
“One-to-one tutoring is often an effective means to help students learn”
- How tutors talk
Instructions and Guide for Diagnostic Questions: The NeurIPS 2020 Education Challenge
The NeurIPS 2020 challenge on Eedi diagnostic questions, where wrong answer choices reveal specific misconceptions.
“the answers that the students give to these questions reveal key information about the specific nature of misconceptions”
- How tutors talk
Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions
Measures how teachers build on what students say, and links that uptake to outcomes.
“teachers' uptake of student contributions has been linked to higher student achievement”
- How tutors talk
Is it a good move? Mining effective tutoring strategies from human-human tutorial dialogues
Mines human tutoring dialogues to find which tutor moves go with better learning.
- How tutors talk
The TalkMoves Dataset: K-12 Mathematics Lesson Transcripts Annotated for Teacher and Student Discursive Moves
567 K-12 math lesson transcripts labelled for teacher and student talk moves from accountable talk theory.
“sustained classroom discourse is a critical component of equitable, engaging, and rich learning environments”
- How tutors talk
The NCTE Transcripts: A Dataset of Elementary Math Classroom Transcripts
Dialogic teacher moves track with better observation scores and learning outcomes.
“these moves are correlated with better classroom observation scores and learning outcomes”
- How tutors talk
Is ChatGPT a Good Teacher Coach? Measuring Zero-Shot Performance For Scoring and Providing Actionable Insights on Classroom Instruction
Tests whether ChatGPT can score classroom transcripts and give teachers useful coaching feedback.
“We explore whether generative AI could become a cost-effective complement to expert feedback by serving as an automated teacher coach”
- How tutors talk
Can Automated Feedback Improve Teachers’ Uptake of Student Ideas? Evidence From a Randomized Controlled Trial in a Large-Scale Online Course
A randomized trial with 1,136 instructors: automated feedback on uptake of student ideas made instructors build on students more.
“We find that M-Powering Teachers improves instructors' uptake of student contributions by 13%”
- How tutors talk
Using Large Language Models to Assess Tutors' Performance in Reacting to Students Making Math Errors
Checks whether GPT-3.5 and GPT-4 can grade how real tutors respond when a student makes a math error.
“Rather than drawing direct attention to the error, tutors should guide the students to identify and correct their mistakes on their own”
- How tutors talk
LLM Based Math Tutoring: Challenges and Dataset
A dataset for checking whether LLM tutors get the math right while tutoring, plus a look at the kinds of student interactions.
“evaluating their performance in real-time math tutoring scenarios presents distinct challenges”
- How tutors talk
Edu-ConvoKit: An Open-Source Library for Education Conversation Data
An open-source library for cleaning, annotating and analyzing conversation data from classrooms and tutoring.
“an open-source library designed to handle pre-processing, annotation and analysis of conversation data in education”
- Intelligent tutoring systems
Knowledge tracing: Modeling the acquisition of procedural knowledge
Bayesian knowledge tracing: a tutor estimates, skill by skill, how likely the student is to know it, and updates after every answer.
- Intelligent tutoring systems
Intelligent Tutoring Goes To School in the Big City
An algebra tutor in Pittsburgh city schools raised standardized test scores.
- Intelligent tutoring systems
AutoTutor: A simulation of a human tutor
A computer tutor that holds natural-language dialogue like a human tutor.
- Intelligent tutoring systems
Performance Factors Analysis - A New Alternative to Knowledge Tracing
Performance Factors Analysis, a simple alternative to knowledge tracing that counts a student's past successes and failures per skill.
- Intelligent tutoring systems
The Knowledge-Learning-Instruction Framework: Bridging the Science-Practice Chasm to Enhance Robust Student Learning
The Knowledge-Learning-Instruction framework: match the kind of instruction to the kind of knowledge and learning involved.
“we describe the Knowledge-Learning-Instruction (KLI) framework”
- Intelligent tutoring systems
The ASSISTments Ecosystem: Building a Platform that Brings Scientists and Teachers Together for Minimally Invasive Research on Human Learning and Teaching
ASSISTments, a free platform where teachers assign problems with hints and students get immediate feedback, also used for research.
“The system gives immediate feedback to students while they are working”
- Intelligent tutoring systems
Intelligent tutoring systems and learning outcomes: A meta-analysis
A meta-analysis of 107 effect sizes comparing learning with intelligent tutoring systems to other kinds of instruction.
“107 effect sizes involving 14,321 participants were extracted and analyzed”
- Intelligent tutoring systems
AutoTutor and Family: A Review of 17 Years of Natural Language Tutoring
Conversational tutoring produced learning gains in physics, computer literacy and more.
“AutoTutor is a natural language tutoring system that has produced learning gains across multiple domains”
- Intelligent tutoring systems
Deep Knowledge Tracing
Uses recurrent neural networks to model what a student knows from their sequence of answers.
“we explore the utility of using Recurrent Neural Networks (RNNs) to model student learning”
- Intelligent tutoring systems
Effectiveness of Intelligent Tutoring Systems: A Meta-Analytic Review
A meta-analysis of 50 controlled evaluations of intelligent tutoring systems.
“The median effect of intelligent tutoring in the 50 evaluations was to raise test scores 0.66 standard deviations over conventional levels”
- Intelligent tutoring systems
Online Mathematics Homework Increases Student Achievement
A randomized trial with 2,850 seventh graders in Maine: online homework with timely feedback and hints raised math scores.
“Results showed that the intervention significantly increased student scores on an end-of-the-year standardized mathematics assessment”
- Intelligent tutoring systems
Dynamic Key-Value Memory Networks for Knowledge Tracing
A memory network for knowledge tracing that outputs a mastery level for each concept.
“directly output a student's mastery level of each concept”
- Intelligent tutoring systems
A Self-Attentive model for Knowledge Tracing
A self-attention model for knowledge tracing that handles sparse student data better than earlier neural models.
“Knowledge tracing is the task of modeling each student's mastery of knowledge concepts”
- Intelligent tutoring systems
EdNet: A Large-Scale Hierarchical Dataset in Education
A large public dataset of student interactions from an English test-prep tutor, for knowledge tracing research.
“there is no public large-scale benchmark dataset”
- Intelligent tutoring systems
Context-Aware Attentive Knowledge Tracing
Attentive knowledge tracing with interpretable parts from cognitive and psychometric models, including decay of what was learned.
“predicting future learner performance given their past performance in educational applications”
- Explanations, analogies and misconceptions
Analogical problem solving
A solved story helps crack an analogous problem, mostly when learners are hinted.
- Explanations, analogies and misconceptions
Accommodation of a scientific conception: Toward a theory of conceptual change
A classic theory of conceptual change: learners give up an idea only when it stops working and a new one makes sense.
“learning is the result of the interaction between what the student is taught and his current ideas or concepts”
- Explanations, analogies and misconceptions
Structure-mapping: A theoretical framework for analogy
Analogies work by mapping relations between domains, not surface features.
“Relations between objects, rather than attributes of objects, are mapped from base to target”
- Explanations, analogies and misconceptions
Force concept inventory
The Force Concept Inventory, a test that shows how common sense beliefs about force survive regular physics teaching.
“Instruction that does not take them into account is almost totally ineffective, at least for the majority of students”
- Explanations, analogies and misconceptions
Mental models of the earth: A study of conceptual change in childhood
Children's ideas about the shape of the Earth show consistent mental models that mix what they are told with what they see.
“many children said that the earth is round but also stated that it has an end or edge from which people could fall”
- Explanations, analogies and misconceptions
Toward an Epistemology of Physics
Describes intuitive physics as many small pieces of knowledge (p-prims) that learning has to reorganize.
- Explanations, analogies and misconceptions
From things to processes: A theory of conceptual change for learning science concepts
Argues that some science ideas are hard because students treat processes, like heat or current, as if they were things.
- Explanations, analogies and misconceptions
The misunderstood limits of folk science: an illusion of explanatory depth
People think they understand how things work much better than they do, until they try to explain it.
“People feel they understand complex phenomena with far greater precision, coherence, and depth than they really do”
- Explanations, analogies and misconceptions
Learning and transfer: A general role for analogical encoding
Comparing two cases side by side helped learners pull out the shared idea and use it later.
“Experiment 2 showed a marked advantage for comparing two cases over studying the 2 cases separately”
- Explanations, analogies and misconceptions
The structure and function of explanations
A review of how explanations shape learning and generalization by fitting new facts into what we already believe.
“explanations accommodate novel information in the context of prior beliefs, and do so in a way that fosters generalization”
- Explanations, analogies and misconceptions
Cognitive Supports for Analogies in the Mathematics Classroom
Compares how teachers in Hong Kong, Japan and the US support analogies in math lessons.
“Variations in the effective use of analogies in math instruction across countries may contribute to performance differences in the TIMSS studies”
- Explanations, analogies and misconceptions
Why Instructional Explanations Often Do Not Work: A Framework for Understanding the Effectiveness of Instructional Explanations
A framework for why instructional explanations often fail and how to design ones that work.
“research shows that they often do not contribute to learning”
- Explanations, analogies and misconceptions
Selective effects of explanation on learning during early childhood
Asking young children to explain a toy helped them learn how it works more than only watching it.
“explanation promotes causal learning”
- Memory, motivation and metacognition
The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information
The classic paper on the limits of short-term memory and on chunking information to stretch them.
- Memory, motivation and metacognition
Levels of processing: A framework for memory research
Memory depends on how deeply information is processed, not on which store it sits in.
“An alternative framework for human memory research is then outlined in terms of depth or levels of processing”
- Memory, motivation and metacognition
Working Memory
The working memory model: a small active workspace for thinking, not just a short-term store.
- Memory, motivation and metacognition
Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry
The paper that named metacognition: knowing and monitoring your own thinking.
- Memory, motivation and metacognition
Motivational and self-regulated learning components of classroom academic performance
Self-efficacy, self-regulation and strategy use predicted classroom performance for 173 seventh graders.
“Self-efficacy and intrinsic value were positively related to cognitive engagement and performance”
- Memory, motivation and metacognition
Unskilled and unaware of it: How difficulties in recognizing one's own incompetence lead to inflated self-assessments
People with the least skill tend to overrate their skill the most, because judging it needs the same skill.
“participants scoring in the bottom quartile on tests of humor, grammar, and logic grossly overestimated their test performance and ability”
- Memory, motivation and metacognition
Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being
Self-determination theory: people are most motivated when they feel competent, autonomous and related to others.
“The findings have led to the postulate of three innate psychological needs”
- Memory, motivation and metacognition
The magical number 4 in short-term memory: A reconsideration of mental storage capacity
Working memory holds about three to five chunks, fewer than the famous seven.
“it is only three to five chunks”
- Memory, motivation and metacognition
Becoming a Self-Regulated Learner: An Overview
An overview of self-regulated learning: setting goals, using strategies, and checking your own progress.
- Memory, motivation and metacognition
Implicit Theories of Intelligence Predict Achievement Across an Adolescent Transition: A Longitudinal Study and an Intervention
Seventh graders who believed intelligence can grow did better in math over junior high.
“the belief that intelligence is malleable (incremental theory) predicted an upward trajectory in grades over the two years of junior high school”
- Memory, motivation and metacognition
Better to be frustrated than bored: The incidence, persistence, and impact of learners’ cognitive-affective states during interactions with three different computer-based learning environments
Tracks learners' feelings in three computer learning environments; boredom was more persistent and more harmful than frustration.
- Memory, motivation and metacognition
Mind-Set Interventions Are a Scalable Treatment for Academic Underachievement
Short online growth mindset and purpose lessons raised grades for students at risk of dropping out.
“delivered brief growth-mind-set and sense-of-purpose interventions through online modules to 1,594 students in 13 geographically diverse high schools”
- Memory, motivation and metacognition
To What Extent and Under Which Circumstances Are Growth Mind-Sets Important to Academic Achievement? Two Meta-Analyses
Two meta-analyses found weak overall links between growth mindset and achievement, stronger for some groups.
“Overall effects were weak”
- Memory, motivation and metacognition
A national experiment reveals where a growth mindset improves achievement
A national randomized experiment: a short online growth mindset lesson raised grades for lower-achieving students.
“improved grades among lower-achieving students and increased overall enrolment to advanced mathematics courses”
A Time For Telling
Comparing contrasting cases first prepares students to learn from a later lecture.
How People Learn: Brain, Mind, Experience, and School: Expanded Edition
Synthesis of learning science: how experts differ from novices and how transfer works.
The Hidden Lives of Learners
Decades of classroom recordings show peers and private worlds shape what students learn.
Productive Failure
Students who struggled first with hard problems later transferred knowledge better.
“suggesting a latent productivity in what initially seemed to be failure”
The ICAP Framework: Linking Cognitive Engagement to Active Learning Outcomes
Learning rises from passive to active to constructive to interactive engagement.
“from passive to active to constructive to interactive, their learning will increase”
Active learning increases student performance in science, engineering, and mathematics
Across 225 studies, active learning raised exam scores and cut failure rates.
“student performance on examinations and concept inventories increased by 0.47 SDs under active learning”
Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom
Students in active classes learned more but felt they learned less.
“when students experience the increased cognitive effort associated with active learning, they initially take that effort to signify poorer learning”
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