A multimedia Adaptive tutoring system for mathematics that addresses cognition, metacognition and affect
Open accessAbstract
This article describes research results based on multiple years of experimentation and real-world experience with an adaptive tutoring system named Wayang Outpost. The system represents a novel adaptive learning technology that has shown successful outcomes with thousands of students, and provided teachers with valuable information about students’ mathematics performance. We define progress in three areas: improved student cognition, engagement, and affect, and we attribute this improvement to specific components and interventions that are inherently affective, cognitive, and metacognitive in nature. For instance, improved student cognitive outcomes have been measured with pre-post tests and state standardized tests, and achieved due to personalization of content and math fluency training. Improved student engagement was achieved by supporting students’ metacognition and motivation via affective learning companions and progress reports, measured via records of student gaming of the system. Student affect within the tutor was measured through sensors and student self-reports, and supported through affective learning companions and progress reports. Collectively, these studies elucidate a suite of effective strategies to support advanced personalized learning via an intelligent adaptive tutor that can be tailored to the individual needs, emotions, cognitive states, and metacognitive skills of learners.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Only one paper from 2014 surveyed other aspects of motivation (e.g., self-efficacy) in a more substantial way.
“As far as we can tell, only one paper from 2014 surveyed other aspects of motivation (e.g., self-efficacy) in a more substantial way (Arroyo et al., 2014).”
From Evolution and Revolution in Artificial Intelligence in Education (2016) · cites this paper as Arroyo et al., 2014
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
(1978) · Medical Entomology and Zoology · Cited by 53,488 · see citing works
Baddeley, A. D., & Hitch, G. (1974) · Psychology of Learning and Motivation · doi:10.1016/s0079-7421(08)60452-1 · Cited by 9,860 · see citing works
Mayer, R. (2020) · doi:10.1017/9781316941355 · Cited by 7,777 · see citing works
Building a practically useful theory of goal setting and task motivation: A 35-year odyssey.
Locke, E. A., & Latham, G. P. (2002) · American Psychologist · doi:10.1037/0003-066x.57.9.705 · Cited by 7,766 · cited 1× · see citing works
“2003), understanding which problem solving strategies to apply, and setting manageable goals and objectives for one-self (Locke and Latham 2002).”
BackgroundProbabilistic Models for Some Intelligence and Attainment Tests
Psychology, M. (1961) · Information and Control · doi:10.1016/s0019-9958(61)80061-2 · Cited by 6,936 · see citing works
(1999) · Cited by 6,308 · see citing works
Pekrun, R. (2006) · Educational Psychology Review · doi:10.1007/s10648-006-9029-9 · Cited by 5,566 · cited 8× · see citing works
“…theory of emotion existed that addressed learning, explained which emotions are most important in learning, or identified how emotion influenced learning (Picard et al. 2004), though later work by Pekrun solidified that idea that our intuitions were headed in the right direction (Pekrun 2006).”
BackgroundMethodResultInfluentialHandbook of educational psychology
(1997) · Choice Reviews Online · doi:10.5860/choice.34-3084 · Cited by 4,850 · see citing works
Self-Efficacy: An Essential Motive to Learn
Zimmerman, B. J. (2000) · Contemporary Educational Psychology · doi:10.1006/ceps.1999.1016 · Cited by 4,294 · see citing works
Self-Efficacy and Academic Motivation
Schunk, D. H. (1991) · Educational Psychologist · doi:10.1080/00461520.1991.9653133 · Cited by 4,292 · see citing works
Cognitive Apprenticeship: Teaching the Crafts of Reading, Writing, and Mathematics
Collins, A., Brown, J. S., & Newman, S. E. (2018) · Knowing, Learning, and Instruction · doi:10.4324/9781315044408-14 · Cited by 3,674 · see citing works
Feedback and Self-Regulated Learning: A Theoretical Synthesis
Butler, D. L., & Winne, P. H. (1995) · Review of Educational Research · doi:10.3102/00346543065003245 · Cited by 3,334 · see citing works
Handbook of Educational Psychology
Berliner, D. C., & Calfee, R. C. (2013) · Routledge eBooks · doi:10.4324/9780203053874 · Cited by 3,212 · see citing works
Knowledge tracing: Modeling the acquisition of procedural knowledge
Corbett, A. T., & Anderson, J. R. (1995) · User Modelling and User-Adapted Interaction · doi:10.1007/bf01099821 · Cited by 2,324 · see citing works
Mayer, R. E. (2001) · doi:10.1017/cbo9781139164603 · Cited by 2,304 · see citing works
Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications
Calvo, R. A., & D'Mello, S. (2010) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2010.1 · Cited by 1,893 · cited 1× · see citing works
“The learning sciences community acknowledges the importance of affect in students’ experiences with educational systems and has developed technologies that can automatically detect and respond to student affect (Arroyo et al. 2009a; Calvo and D’Mello 2010; Conati and Maclaren 2009; Cooper et al. 2010; Graesser et al.…”
BackgroundKnowing, Learning, and Instruction
(2018) · Routledge eBooks · doi:10.4324/9781315044408 · Cited by 1,819 · see citing works
Praise for intelligence can undermine children's motivation and performance.
Mueller, C. M., & Dweck, C. S. (1998) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.75.1.33 · Cited by 1,709 · cited 2× · see citing works
“They also had significantly higher mastery learning orientation scores, as measured by two survey questions based on ones by Mueller and Dweck (1998), indicating that students who saw Progress Charts and Tips had a greater desire to learn for the sake of learning.”
MethodBull, R., & Scerif, G. (2001) · Developmental Neuropsychology · doi:10.1207/s15326942dn1903_3 · Cited by 1,501 · cited 1× · see citing works
“as working memory capacity and executive function (Bull and Scerif 2001).”
The Control-Value Theory of Achievement Emotions
Pekrun, R. H., Frenzel, A. C., Goetz, T., & Perry, R. P. (2007) · Elsevier eBooks · doi:10.1016/b978-012372545-5/50003-4 · Cited by 1,344 · see citing works
Establishing and maintaining long-term human-computer relationships
Bickmore, T. W., & Picard, R. W. (2005) · ACM Transactions on Computer-Human Interaction · doi:10.1145/1067860.1067867 · Cited by 1,333 · cited 2× · see citing works
“Research has shown that by encouraging team relationships between humans and computers, people can be influenced to think that the information from the computer is of better quality and relayed in a more friendly way (Bickmore and Picard 2004; Nass et al. 1996).”
BackgroundPekrun, R. H., Goetz, T., Daniels, L. M., Stupnisky, R. H., & Perry, R. P. (2010) · Journal of Educational Psychology · doi:10.1037/a0019243 · Cited by 1,239 · see citing works
Intelligent Tutoring Goes To School in the Big City
Koedinger, K. R., Anderson, J. R., Hadley, W. H., & Mark, M. A. (2018) · doi:10.1184/r1/6470153 · Cited by 1,105 · see citing works
Mathematics in the streets and in schools
Carraher, T. N., Carraher, D. W., & Schliemann, A. D. (1985) · British Journal of Developmental Psychology · doi:10.1111/j.2044-835x.1985.tb00951.x · Cited by 1,054 · see citing works
Women's underrepresentation in science: sociocultural and biological considerations
Ceci, S. J., Williams, W. M., & Barnett, S. M. (2009) · Psychological Bulletin · doi:10.1037/a0014412 · Cited by 957 · see citing works
How can primary school students learn self-regulated learning strategies most effectively?
Dignath, C., Buettner, G., & Langfeldt, H.-P. (2008) · Educational Research Review · doi:10.1016/j.edurev.2008.02.003 · Cited by 903 · cited 2× · see citing works
“In a meta-analysis of selfregulatory training programs, (Dignath et al. 2008) summarized evidence that by addressing self-regulation during learning, students’ academic performance, strategy use, and motivational outcomes were improved.”
BackgroundProceedings of the 7th International Conference on Educational Data Mining.
Stamper, J. C., Pardos, Z. A., Mavrikis, M., & McLaren, B. M. (2014) · Educational Data Mining · Cited by 667 · see citing works
Nass, C., Fogg, B. J., & Moon, Y. (1996) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.1996.0073 · Cited by 665 · see citing works
Help Seeking and Help Design in Interactive Learning Environments
Aleven, V., Stahl, E., Schworm, S., Fischer, F., & Wallace, R. (2003) · Review of Educational Research · doi:10.3102/00346543073003277 · Cited by 609 · see citing works
Handbook of Educational Data Mining
Mavrikis, M., D'Mello, S., Porayska‐Pomsta, K., Cocea, M., & Graesser, A. C. (2010) · CRC Press eBooks · doi:10.1201/b10274 · Cited by 586 · see citing works
Koedinger, K., Aleven, V., Roll, I., & Baker, R. (2009) · Routledge eBooks · doi:10.4324/9780203876428-29 · Cited by 580 · see citing works
Theories and Principles of Motivation
Berliner, D. C., & Calfee, R. C. (2013) · Routledge eBooks · doi:10.4324/9780203053874-10 · Cited by 540 · see citing works
Affective Learning — A Manifesto
Picard, R. W., Papert, S. A., Bender, W. R., Blumberg, B. M., Breazeal, C., Cavallo, D. P., Machover, T., Resnick, M., Roy, D. K., & Strohecker, C. (2004) · BT Technology Journal · doi:10.1023/b:bttj.0000047603.37042.33 · Cited by 511 · see citing works
Greene, J. A., & Azevedo, R. (2007) · Review of Educational Research · doi:10.3102/003465430303953 · Cited by 486 · see citing works
Off-task behavior in the cognitive tutor classroom
Baker, R. S., Corbett, A. T., Koedinger, K. R., & Wagner, A. Z. (2004) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/985692.985741 · Cited by 456 · see citing works
Mazzocco, M. M. M., Feigenson, L., & Halberda, J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0023749 · Cited by 420 · see citing works
Toward Meta-cognitive Tutoring: A Model of Help Seeking with a Cognitive Tutor
Aleven, V., McLaren, B. M., Roll, I., & Koedinger, K. R. (2006) · International Journal of Artificial Intelligence in Education · doi:10.3233/irg-2006-16(2)02 · Cited by 409 · see citing works
Improving academic achievement: Impact of psychological factors on education
Aronson, J. M. (2002) · Cited by 397 · see citing works
Ivon, A., Cooper David, G., Winslow, B., Park, W. B., Kasia, M., & Robert, C. (2009) · Frontiers in Artificial Intelligence and Applications · doi:10.3233/978-1-60750-028-5-17 · Cited by 382 · see citing works
Affect-aware tutors: recognising and responding to student affect
Woolf, B., Burleson, W., Arroyo, I., Dragon, T., Cooper, D., & Picard, R. (2009) · International Journal of Learning Technology · doi:10.1504/ijlt.2009.028804 · Cited by 371 · see citing works
Self-citationEkman, P. (1999) · doi:10.1002/0470013494.ch16 · Cited by 341 · see citing works
Empirically Building and Evaluating a Probabilistic Model of User Affect
Conati, C., & Maclaren, H. (2009) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-009-9062-8 · Cited by 328 · see citing works
Adaptive Human Scaffolding Facilitates Adolescents’ Self-regulated Learning with Hypermedia
Azevedo, R., Cromley, J. G., Winters, F. I., Moos, D. C., & Greene, J. A. (2005) · Instructional Science · doi:10.1007/s11251-005-1273-8 · Cited by 306 · see citing works
Libertus, M. E., Duong, S., & Silver, A. M. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-809324-5.23573-6 · Cited by 270 · see citing works
Parslow, G. P. (1990) · Biochemical Education · doi:10.1016/0307-4412(90)90227-f · Cited by 257 · see citing works
Dweck, C. (2002) · Elsevier eBooks · doi:10.1016/b978-012064455-1/50006-3 · Cited by 253 · see citing works
Adapting to When Students Game an Intelligent Tutoring System
Baker, R. S., Corbett, A. T., Koedinger, K. R., Evenson, S., Roll, I., Wagner, A. Z., Naim, M., Raspat, J., Baker, D. J., & Beck, J. E. (2006) · Lecture notes in computer science · doi:10.1007/11774303_39 · Cited by 245 · see citing works
Course sequencing techniques for large-scale web-based education
Brusilovsky, P. L., & Vassileva, J. (2003) · International Journal of Continuing Engineering Education and Life-Long Learning · doi:10.1504/ijceell.2003.002154 · Cited by 239 · see citing works
Adaptive Learning Resources Sequencing in Educational Hypermedia Systems
Karampiperis, P., & Sampson, D. G. (2005) · Cited by 233 · see citing works
Gobert, J. D., Sao Pedro, M., Raziuddin, J., & Baker, R. S. (2013) · Journal of the Learning Sciences · doi:10.1080/10508406.2013.837391 · Cited by 210 · see citing works
Developing a generalizable detector of when students game the system
Baker, R. S., Corbett, A. T., Roll, I., & Koedinger, K. R. (2008) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-007-9045-6 · Cited by 204 · see citing works
Who Am I and What Can I Do? Children's Self-Concepts and Motivation in Achievement Situations
Wigfield, A., & Karpathian, M. (1991) · Educational Psychologist · doi:10.1080/00461520.1991.9653134 · Cited by 188 · see citing works
New Perspectives on Affect and Learning Technologies
Calvo, R. A., & D’Mello, S. K. (2011) · Springer eBooks · doi:10.1007/978-1-4419-9625-1 · Cited by 175 · see citing works
Inferring learning and attitudes from a Bayesian Network of log file data
Arroyo, I., & Woolf, B. P. (2005) · Cited by 137 · see citing works
A Time for Emoting: When Affect-Sensitivity Is and Isn’t Effective at Promoting Deep Learning
D’Mello, S. K., Lehman, B. A., Sullins, J., Daigle, R. P., Combs, R., Vogt, K. A., Perkins, L. A., & Graesser, A. C. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13388-6_29 · Cited by 135 · see citing works
Murray, W. R. (2013) · Routledge eBooks · doi:10.4324/9780203056257-6 · Cited by 134 · see citing works
Evaluating the consequences of affective feedback in intelligent tutoring systems
Robison, J. L., McQuiggan, S. W., & Lester, J. C. (2009) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2009.5349555 · Cited by 132 · see citing works
Achieving Affective Impact: Visual Emotive Communication in Lifelike Pedagogical Agents
Lester, J. C., Towns, S., & Fitzgerald, P. (1998) · Cited by 132 · see citing works
Carraher, D. W., & Schliemann, A. D. (2002) · Journal of the Learning Sciences · doi:10.1207/s15327809jls1101_1 · Cited by 130 · see citing works
Repairing Disengagement With Non-Invasive Interventions
Arroyo, I., Ferguson, K., Johns, J., Dragon, T., Meheranian, H., Fisher, D., Barto, A. G., Mahadevan, S., & Woolf, B. P. (2007) · Cited by 126 · see citing works
Toward Measuring and Maintaining the Zone of Proximal Development in Adaptive Instructional Systems
Murray, T., & Arroyo, I. (2002) · Lecture notes in computer science · doi:10.1007/3-540-47987-2_75 · Cited by 119 · see citing works
Designing for metacognition—applying cognitive tutor principles to the tutoring of help seeking
Roll, I., Aleven, V., McLaren, B. M., & Koedinger, K. R. (2007) · Metacognition and Learning · doi:10.1007/s11409-007-9010-0 · Cited by 118 · see citing works
Woolf, B. P., Arroyo, I., Müldner, K., Burleson, W., Cooper, D. G., Dolan, R., & Christopherson, R. M. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13388-6_37 · Cited by 117 · see citing works
Aleven, V. A. W. M. M., Roll, I., McLaren, B. M., & Koedinger, K. R. (2010) · Educational Psychologist · doi:10.1080/00461520.2010.517740 · Cited by 111 · see citing works
A dynamic mixture model to detect student motivation and proficiency
Johns, J., & Woolf, B. P. (2006) · Cited by 104 · see citing works
Lemaire, P., & Lecacheur, M. (2011) · Cognitive Development · doi:10.1016/j.cogdev.2011.01.002 · Cited by 91 · see citing works
2. Beliefs That Make Smart People Dumb
Dweck, C. S. (2017) · Yale University Press eBooks · doi:10.12987/9780300128208-004 · Cited by 84 · see citing works
Arroyo, I., Woolf, B. P., Cooper, D. G., Burleson, W., & Müldner, K. (2011) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt.2011.157 · Cited by 82 · see citing works
Emotions and Learning with AutoTutor
Graesser, A. C., Chipman, P., King, B. G., McDaniel, B., & D’Mello, S. K. (2007) · Cited by 76 · see citing works
Eynde, P. O. ’., Corte, E. D., & Verschaffel, L. (2007) · Elsevier eBooks · doi:10.1016/b978-012372545-5/50012-5 · Cited by 75 · see citing works
Affective Gendered Learning Companions
Arroyo, I., Park, W. B., Royer, J. M., & Minghui, T. (2009) · Frontiers in artificial intelligence and applications · doi:10.3233/978-1-60750-028-5-41 · Cited by 74 · see citing works
Web-Based Intelligent Multimedia Tutoring for High Stakes Achievement Tests
Arroyo, I., Beal, C., Murray, T., Walles, R., & Woolf, B. P. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-30139-4_44 · Cited by 74 · see citing works
Supporting Students’ Self-Regulated Learning with an Open Learner Model in a Linear Equation Tutor
Long, Y., & Aleven, V. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39112-5_23 · Cited by 71 · see citing works
Tronsky, L. N. (2005) · Memory & Cognition · doi:10.3758/bf03193086 · Cited by 68 · see citing works
The effects of empathetic virtual characters on presence in narrative-centered learning environments
McQuiggan, S. W., Rowe, J., & Lester, J. C. (2008) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1357054.1357291 · Cited by 68 · see citing works
Extending Knowledge Tracing to Allow Partial Credit: Using Continuous versus Binary Nodes
Wang, Y., & Heffernan, N. T. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39112-5_19 · Cited by 64 · see citing works
AI and Education: Grand Challenges
Kay, J. (2012) · IEEE Intelligent Systems · doi:10.1109/mis.2012.92 · Cited by 61 · see citing works
Lajoie, S. P., & Lesgold, A. (1989) · eScholarship@McGill (McGill) · Cited by 55 · see citing works
Sensors Model Student Self Concept in the Classroom
Cooper, D. G., Arroyo, I., Woolf, B. P., Müldner, K., Burleson, W., & Christopherson, R. M. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-02247-0_6 · Cited by 48 · see citing works
Roll, I., Aleven, V., McLaren, B. M., & Koedinger, K. R. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-21869-9_38 · Cited by 47 · see citing works
Effort-based Tutoring: An Empirical Approach to Intelligent Tutoring.
Arroyo, I., Meheranian, H., & Woolf, B. P. (2010) · Educational Data Mining · Cited by 43 · see citing works
“Yes!”: Using Tutor and Sensor Data to Predict Moments of Delight during Instructional Activities
Müldner, K., Burleson, W., & VanLehn, K. A. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13470-8_16 · Cited by 39 · see citing works
Mathews, M., Mitrović, A., Lin, B., Holland, J., & Churcher, N. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-30950-2_54 · Cited by 38 · see citing works
Sensor-free automated detection of affect in a Cognitive Tutor for Algebra.
Baker, R. S., Gowda, S. M., Wixon, M., Kalka, J., Wagner, A. Z., Salvi, A., Aleven, V., Kusbit, G. W., Ocumpaugh, J. L., & Rossi, L. M. (2012) · Educational Data Mining · Cited by 38 · see citing works
Using an Intelligent Tutor and Math Fluency Training to Improve Math Performance
Arroyo, I., Royer, J. M., & Woolf, B. P. (2011) · International Journal of Artificial Intelligence in Education · doi:10.3233/jai-2011-020 · Cited by 35 · see citing works
LEARNING DISABILITIES IN BASIC MATHEMATICS Deficits in Memory and Cognition
Geary, D. C., & Hoard, M. K. (2002) · Cited by 33 · see citing works
Ranking Feature Sets for Emotion Models Used in Classroom Based Intelligent Tutoring Systems
Cooper, D. G., Müldner, K., Arroyo, I., Woolf, B. P., & Burleson, W. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13470-8_14 · Cited by 26 · see citing works
Actionable Affective Processing for Automatic Tutor Interventions
Cooper, D. G., Arroyo, I., & Woolf, B. P. (2011) · Springer eBooks · doi:10.1007/978-1-4419-9625-1_10 · Cited by 25 · see citing works
Burleson, W., & Picard, R. W. (2004) · Educational technology: The magazine for managers of change in education · Cited by 23 · see citing works
The Opportunities and Limitations of Scaling Up Sensor-Free Affect Detection
Wixon, M., Arroyo, I., Müldner, K., Burleson, W., Rai, D., & Woolf, B. P. (2014) · Cited by 21 · see citing works
PRELIMINARY EVALUATION OF A NEGOTIABLE STUDENT MODEL IN A CONSTRAINT-BASED ITS
THOMSON, D., & Mitrović, A. (2010) · Research and Practice in Technology Enhanced Learning · doi:10.1142/s1793206810000797 · Cited by 20 · see citing works
An Architecture to Combine Meta-Cognitive and Cognitive Tutoring: Pilot Testing the Help Tutor
Aleven, V., Roll, I., McLaren, B. M., Ryu, E. J., & Koedinger, K. R. (2018) · Figshare · doi:10.1184/r1/6469799 · Cited by 18 · see citing works
1 Bayesian Networks and Linear Regression Models of Students’ Goals, Moods and Emotions
Arroyo, I., Cooper, D. G., Burleson, W., & Woolf, B. P. (2013) · Cited by 15 · see citing works
Keating, D. P. (2011) · Elsevier eBooks · doi:10.1016/b978-0-12-373951-3.00008-9 · Cited by 13 · see citing works
Visualization of Student Activity Patterns within Intelligent Tutoring Systems
Shanabrook, D. H., Arroyo, I., Woolf, B. P., & Burleson, W. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-30950-2_6 · Cited by 12 · see citing works
Preferred Features of Open Learner Models for University Students
Susan Bull, A. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-30950-2_53 · Cited by 11 · see citing works
Teammate Relationships Improve Help-Seeking Behavior in an Intelligent Tutoring System
Tai, M., Arroyo, I., & Woolf, B. P. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39112-5_25 · Cited by 9 · see citing works
Persistent Effects of Social Instructional Dialog in a Virtual Learning Environment
Ogan, A. E., Aleven, V., Jones, C., & Kim, J. M. (2011) · International Conference on Artificial Intelligence in Education · doi:10.1007/978-3-642-21869-9_32 · Cited by 8 · see citing works
Repairing Deactivating Negative Emotions with Student Progress Pages
Rai, D., Arroyo, I., Stephens, L., Lozano, C., Burleson, W., Woolf, B. P., & Beck, J. E. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39112-5_115 · Cited by 6 · see citing works
Link Recommendation in E-Learning Systems Based on Content-Based Student Proles
Godoy, D., & Amandi, A. (2010) · CRC Press eBooks · doi:10.1201/b10274-26 · Cited by 6 · see citing works
Stottler, D., Domeshek, E. A., & Henke, S. (2005) · Cited by 5 · see citing works
Royer, J. M. (2003) · Cited by 4 · see citing works
Flagged first, then by citations
4 of the 106 references couldn’t be matched to a known paper.
Research works printed but not linked: 8
- Azevedo, R., Bouchet, F., Harley, J. M., Feyzi-Behnagh, R., Trevors, G., Duffy, M., Taub, M., Pacampara, N., Agnew, L., Griscom, S., Mudrick, N., Stead, V., & Yang, W. (2011). MetaTutor: An Intelligent Multi-Agent Tutoring System Designed to Detect, Track, Model, and Foster Self-Regulated Learning In Proceedings of the Fourth Workshop on Self-Regulated Learning in Educational Technologies. In conjunction with the 15th International Conference onArtificial Intelligence on Education (AIED 2011)
- Bull, S., Wasson, B., Johnson, M. D., Petters, D., & Hansen, C. (2012). Helping teachers effectively support group learning. In Proceedings of Workshop on Intelligent Support for Learning in Groups, Intelligent Tutoring Systems
- Hartfield, E. (1994). Emotional contagion. United Kingdom: Cambridge University Press.
- Heffernan, N., Militello, M., Heffernan, C., & Decoteau, M. (2012) Effective and meaningful use of educational technology: three cases from the classroom. In C. Dede & J. Richards (Eds.), Digital Teaching Platforms (pp. 88-102).
- Ogan, A., Aleven, V., Jones, C., & Kim, J. (2011). Pervasive social effects of agent-based instructional dialog. In In Proceedings of the 15th International Conference on Artificial Intelligence in Education (AIED 2011) (pp. 238-246).
- Roll, I., Aleven, V., McLaren, B., & Koedinger, K. (2007). Designing for metacognition -applying Cognitive Tutor principles to metacognitive tutoring. Metacognition and Learning, 2(2-3), 125-140.
- Royer, J. M., & Walles, R. (2007). Influences of gender, motivation and socioeconomic status on mathematics performance. In D. B. Berch & M. Mazzocco (Eds.), Why is math so hard for some children (pp. 349- 368). Baltimore: Paul H. Brookes Publishing Co.
- Woolf, B. (2009). Building Intelligent Tutors: Bridging Theory and Practice. San Francisco: Elsevier Inc./
Cited by
Sorted by citations
Evolution and Revolution in Artificial Intelligence in Education
Roll, I., & Wylie, R. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0110-3 · Cited by 1,229 · see citing works
Bernacki, M. L., Greene, M. J., & Lobczowski, N. G. (2021) · Educational Psychology Review · doi:10.1007/s10648-021-09615-8 · Cited by 545 · see citing works
Stupid tutoring systems, intelligent humans
Baker, R. S. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0105-0 · Cited by 425 · see citing works
Empowering Educators to Be AI-Ready
Luckin, R., Cukurova, M., Kent, C., & du Boulay, B. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100076 · Cited by 422 · see citing works
Ng, D. T. K., Wu, W., Leung, J. K. L., Chiu, T. K. F., & Chu, S. K. W. (2024) · British Journal of Educational Technology · doi:10.1111/bjet.13411 · Cited by 390 · see citing works
Out of the laboratory and into the classroom: the future of artificial intelligence in education
Schiff, D. (2021) · AI & SOCIETY · doi:10.1007/s00146-020-01033-8 · Cited by 334 · see citing works
Understanding the implementation of personalized learning: A research synthesis
Ling, Z., Basham, J. D., & Yang, S. (2020) · Educational Research Review · doi:10.1016/j.edurev.2020.100339 · Cited by 317 · see citing works
Help Helps, But Only So Much: Research on Help Seeking with Intelligent Tutoring Systems
Aleven, V., Roll, I., McLaren, B. M., & Koedinger, K. R. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-015-0089-1 · Cited by 258 · see citing works
Major, L., Francis, G. A., & Tsapali, M. (2021) · British Journal of Educational Technology · doi:10.1111/bjet.13116 · Cited by 318 · see citing works
Affordances and challenges of artificial intelligence in K-12 education: a systematic review
Crompton, H., Jones, M. V., & Burke, D. (2024) · Journal of Research on Technology in Education · doi:10.1080/15391523.2022.2121344 · Cited by 213 · see citing works
Applications of the Elo rating system in adaptive educational systems
Pelánek, R. (2016) · Computers & Education · doi:10.1016/j.compedu.2016.03.017 · Cited by 168 · see citing works
Example-Tracing Tutors: Intelligent Tutor Development for Non-programmers
Aleven, V., McLaren, B. M., Sewall, J., van Velsen, M., Popescu, O., Demi, S., Ringenberg, M. A., & Koedinger, K. R. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-015-0088-2 · Cited by 139 · see citing works
Sarıtepeci, M., & Durak, H. Y. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12829-2 · Cited by 136 · see citing works
Proactive and reactive engagement of artificial intelligence methods for education: a review
Mallik, S., & Gangopadhyay, A. (2023) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2023.1151391 · Cited by 139 · see citing works
The intertwined histories of artificial intelligence and education
Doroudi, S. (2023) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-022-00313-2 · Cited by 129 · see citing works
Reinhold, F., Hoch, S., Werner, B., Richter-Gebert, J., & Reiss, K. M. (2019) · Learning and Instruction · doi:10.1016/j.learninstruc.2019.101264 · Cited by 156 · see citing works
Adaptive feedback in computer-based learning environments: a review
Bimba, A. T., Idris, N. B., Al-Hunaiyyan, A. A., Mahmud, R. B., & Shuib, L. M. (2017) · Adaptive Behavior · doi:10.1177/1059712317727590 · Cited by 123 · see citing works
Zheng, L., Long, M., Zhong, L., & Gyasi, J. F. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-11092-7 · Cited by 116 · see citing works
Evaluating Artificial Intelligence in Education for Next Generation
Joshi, S., Rambola, R. K., & Churi, P. P. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1714/1/012039 · Cited by 139 · see citing works
There are Open Learner Models About!
Susan Bull, A. (2020) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2020.2978473 · Cited by 91 · see citing works
Xhakaj, F., Aleven, V., & McLaren, B. M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66610-5_23 · Cited by 81 · see citing works
Using Robotics to Enhance Active Learning in Mathematics: A Multi-Scenario Study
López-Caudana, E. O., Soledad, M., Pérez, S. M., & Rodríguez-Abitia, G. (2020) · Mathematics · doi:10.3390/math8122163 · Cited by 80 · see citing works
Escape from the Skinner Box: The case for contemporary intelligent learning environments
du Boulay, B. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12860 · Cited by 80 · see citing works
Metrics for Evaluation of Student Models
Pelánek, R. (2015) · Educational Data Mining · doi:10.5281/zenodo.3554665 · Cited by 106 · see citing works
Implementation of technology-supported personalized learning—its impact on instructional quality
Schmid, R., Pauli, C., Стеблер, Р., Reusser, K., & Petko, D. (2022) · The Journal of Educational Research · doi:10.1080/00220671.2022.2089086 · Cited by 91 · see citing works
Koć‐Januchta, M., Schönborn, K. J., Tibell, L. A. E., Chaudhri, V. K., & Heller, H. C. (2020) · Journal of Educational Computing Research · doi:10.1177/0735633120921581 · Cited by 69 · see citing works
Adapting Progress Feedback and Emotional Support to Learner Personality
Dennis, M., Masthoff, J., & Mellish, C. (2015) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-015-0059-7 · Cited by 67 · see citing works
Predicting learners' effortful behaviour in adaptive assessment using multimodal data
Sharma, K., Papamitsiou, Z. K., Olsen, J. K., & Giannakos, M. N. (2020) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3375462.3375498 · Cited by 66 · see citing works
Implementation of Adaptive Learning Systems: Current State and Potential
Imhof, C., Bergamin, P. B., & McGarrity, S. (2020) · Cognition and exploratory learning in the digital age · doi:10.1007/978-3-030-48190-2_6 · Cited by 65 · see citing works
The potential of learning with (and not from) artificial intelligence in education
Chichekian, T., & Benteux, B. (2022) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2022.903051 · Cited by 75 · see citing works
Ashwin, T., & Guddeti, R. R. (2020) · User modeling and user-adapted interaction · doi:10.1007/s11257-019-09254-3 · Cited by 63 · see citing works
Promoting Personalized Learning in Flipped Classrooms: A Systematic Review Study
Çevikbaş, M., & Kaiser, G. (2022) · Sustainability · doi:10.3390/su141811393 · Cited by 73 · see citing works
Artificial Intelligence in Education and Ethics
du Boulay, B. (2023) · Handbook of Open, Distance and Digital Education · doi:10.1007/978-981-19-2080-6_6 · Cited by 56 · see citing works
Personalized learning in iSTART: Past modifications and future design
McCarthy, K. S., Watanabe, M., Dai, J., & McNamara, D. S. (2020) · Journal of Research on Technology in Education · doi:10.1080/15391523.2020.1716201 · Cited by 53 · see citing works
Innovative Learning Environments in STEM Higher Education
Ryoo, J., & Winkelmann, K. (2021) · SpringerBriefs in statistics · doi:10.1007/978-3-030-58948-6 · Cited by 63 · see citing works
Teklu, S. W., & Terefe, B. B. (2022) · Scientific Reports · doi:10.1038/s41598-022-15376-3 · Cited by 49 · see citing works
Delgado, K. A. M., Origgi, J. M., Hasanpoor, T., Yu, H., Allessio, D., Arroyo, I., Lee, W., Betke, M., Woolf, B. P., & Bargal, S. A. (2021) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw54120.2021.00405 · Cited by 44 · see citing works
Fernández-Herrero, J., Gomez‐Donoso, F., & Roig-Vila, R. (2023) · British Journal of Educational Technology · doi:10.1111/bjet.13326 · Cited by 41 · see citing works
Toward Asset-based Instruction and Assessment in Artificial Intelligence in Education
Ocumpaugh, J. L., Roscoe, R. D., Baker, R. S., Hutt, S. J., & Aguilar, S. J. (2024) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-023-00382-x · Cited by 45 · see citing works
Personalized learning and ESSA: What we know and where we go
Zhang, L., Yang, S., & Carter, R. A. (2020) · Journal of Research on Technology in Education · doi:10.1080/15391523.2020.1728448 · Cited by 38 · see citing works
Salmeron-Majadas, S., Baker, R., Santos, O., & Boticario, J. (2018) · IEEE Access · doi:10.1109/access.2018.2854966 · Cited by 32 · see citing works
IRT-Based Adaptive Hints to Scaffold Learning in Programming
Ueno, M., & Miyazawa, Y. (2017) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2017.2741960 · Cited by 34 · see citing works
Digital Disruption In Teaching And Testing
Wyatt‐Smith, C., Lingard, B., & Heck, E. (2021) · Routledge eBooks · doi:10.4324/9781003045793 · Cited by 37 · see citing works
Enhancing learning by Open Learner Model (OLM) driven data design
Kay, J., Bartimote-Aufflick, K., Kitto, K., Kummerfeld, B., Liu, D., & Reimann, P. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100069 · Cited by 39 · see citing works
Bringula, R. P., Fosgate, I. C. O., Garcia, N. P. R., & Yorobe, J. L. M. (2017) · Journal of Educational Computing Research · doi:10.1177/0735633117722494 · Cited by 35 · see citing works
Combining intelligent tutoring systems and gamification: a systematic literature review
Ramadhan, A., Warnars, H. L. H. S., & Razak, F. H. A. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-12092-x · Cited by 33 · see citing works
Artificial Intelligence and Machine Learning: An Instructor’s Exoskeleton in the Future of Education
August, S. E., & Tsaima, A. (2021) · SpringerBriefs in statistics · doi:10.1007/978-3-030-58948-6_5 · Cited by 32 · see citing works
Zhang, L., Carter, R. A., Basham, J. D., & Yang, S. (2022) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12725 · Cited by 31 · see citing works
Some insights into the impact of affective information when delivering feedback to students
Cabestrero, R., Quirós, P., Santos, O., Salmeron-Majadas, S., Uria-Rivas, R., Boticario, J., Arnau, D., Arevalillo-Herráez, M., & Ferri, F. (2018) · Behavior and Information Technology · doi:10.1080/0144929x.2018.1499803 · Cited by 28 · see citing works
Improving metacognition through self-explication in a digital self-regulated learning tool
Braad, E., Degens, N., Barendregt, W., & IJsselsteijn, W. A. (2022) · Educational Technology Research and Development · doi:10.1007/s11423-022-10156-2 · Cited by 46 · see citing works
Arroyo, I., Micciolo, M., Casano, J. D. L., Ottmar, E., Hulse, T., & Rodrigo, M. M. T. (2017) · Annual Symposium on Computer-Human Interaction in Play · doi:10.1145/3116595.3116637 · Cited by 32 · see citing works
Gaur, A. S., Sharan, H. O., & Kumar, R. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-2964-1.ch003 · Cited by 29 · see citing works
Artificial Intelligence in Education and Ethics
du Boulay, B. (2022) · Handbook of Open, Distance and Digital Education · doi:10.1007/978-981-19-0351-9_6-2 · Cited by 28 · see citing works
A Dashboard to Support Teachers During Students’ Self-paced AI-Supported Problem-Solving Practice
Aleven, V., Blankestijn, J., Lawrence, L., Nagashima, T., & Taatgen, N. (2022) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-16290-9_2 · Cited by 28 · see citing works
Adaptive Learning is Hard: Challenges, Nuances, and Trade-offs in Modeling
Pelánek, R. (2024) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-024-00400-6 · Cited by 35 · see citing works
Chopra, A., Patel, H., Rajput, D. S., & Bansal, N. (2024) · Applied Intelligence and Informatics. · doi:10.1007/978-981-97-0914-4_15 · Cited by 27 · see citing works
Integrating affective learning into intelligent tutoring systems
Jiménez, S., Juárez‐Ramírez, R., Castillo, V. H., & Noriega, A. D. R. (2017) · Universal Access in the Information Society · doi:10.1007/s10209-017-0524-1 · Cited by 26 · see citing works
ATL-BP: A Student Engagement Dataset and Model for Affect Transfer Learning for Behavior Prediction
Ruiz, N., Yu, H., Allessio, D., Jalal, M., Joshi, A., Murray, T., Magee, J., Delgado, K. A. M., Ablavsky, V., Sclaroff, S., et al. (2022) · IEEE Transactions on Biometrics Behavior and Identity Science · doi:10.1109/tbiom.2022.3210479 · Cited by 24 · see citing works
Addressing Student Behavior and Affect with Empathy and Growth Mindset.
Karumbaiah, S., Lizarralde, R., Allessio, D., Woolf, B. P., Arroyo, I., & Wixon, N. (2017) · Cited by 23 · see citing works
Student Modeling for Individuals and Groups: the BioWorld and HOWARD Platforms
Lajoie, S. P. (2020) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-020-00219-x · Cited by 23 · see citing works
Chen, L., Chang, H., Rudoler, J., Arnardóttir, E., Zhang, Y., Angeles, C. D. L., & Menon, V. (2022) · npj Science of Learning · doi:10.1038/s41539-022-00146-7 · Cited by 29 · see citing works
The Impact of Gender in Learning With Games
Nguyen, H. A., Hou, X., Richey, J. E., & McLaren, B. M. (2022) · International Journal of Game-Based Learning · doi:10.4018/ijgbl.309128 · Cited by 27 · see citing works
Do better in math: How your body posture may change stereotype threat response
Peper, E., Harvey, R., Mason, L., & Lin, I. (2018) · NeuroRegulation · doi:10.15540/nr.5.2.67 · Cited by 21 · see citing works
Fukuda, M., Hajian, S., Jain, M., Liu, A. L., Obaid, T., Nesbit, J. C., & Winne, P. H. (2022) · International Journal of Science Education · doi:10.1080/09500693.2022.2062799 · Cited by 20 · see citing works
Zhong, L. (2022) · Smart Learning Environments · doi:10.1186/s40561-022-00219-5 · Cited by 20 · see citing works
Motivational and metacognitive feedback in SQL-Tutor*
Hull, A., & du Boulay, B. (2015) · Computer Science Education · doi:10.1080/08993408.2015.1033143 · Cited by 20 · see citing works
Kooken, J. W., Zaini, R. M., & Arroyo, I. (2021) · Metacognition and Learning · doi:10.1007/s11409-020-09252-6 · Cited by 19 · see citing works
Artificial Intelligence in Education and Ethics
du Boulay, B. (2022) · Handbook of Open, Distance and Digital Education · doi:10.1007/978-981-19-0351-9_6-1 · Cited by 19 · see citing works
Developing a Teacher Dashboard For Use with Intelligent Tutoring Systems.
Aleven, V., Xhakaj, F., Holstein, K., & McLaren, B. M. (2016) · Cited by 18 · see citing works
Young learners’ motivation, self-regulation and performance in personalized learning
Ackermans, K., Bakker, M., van Loon, A., Kral, M., & Camp, G. (2024) · Computers & Education · doi:10.1016/j.compedu.2024.105208 · Cited by 33 · see citing works
Künstliche Intelligenz in der Hochschulbildung
Schmohl, T., Watanabe, A., & Schelling, K. (2023) · Hochschulbildung: Lehre und Forschung · doi:10.14361/9783839457696 · Cited by 37 · see citing works
Affect-Aware Adaptive Tutoring Based on Human–Automation Etiquette Strategies
Yang, E., & Dorneich, M. C. (2018) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720818765266 · Cited by 17 · see citing works
Active Learning for Student Affect Detection
Yang, T.-Y., Baker, R. S., Studer, C., Heffernan, N. T., & Lan, A. (2019) · Repository for Publications and Research Data (ETH Zurich) · doi:10.3929/ethz-b-000461351 · Cited by 17 · see citing works
Janning, R., Schatten, C., & Schmidt-Thieme, L. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0097-9 · Cited by 17 · see citing works
Baker, R. S., Richey, J. E., Zhang, J., Karumbaiah, S., Andres-Bray, J. M. L., Nguyen, H. A., Andres, J. M. A. L., & McLaren, B. M. (2024) · Instructional Science · doi:10.1007/s11251-024-09679-3 · Cited by 16 · see citing works
Accessible mathematics videos for non-disabled students in primary education
Ascaso, A. R., Letón, E., Muñoz-Carenas, J., & Finat, C. (2018) · PLoS ONE · doi:10.1371/journal.pone.0208117 · Cited by 16 · see citing works
Künstliche Intelligenz in der Hochschulbildung
(2023) · transcript Verlag eBooks · doi:10.1515/9783839457696 · Cited by 16 · see citing works
An Overview of the Growth and Trends of Current Research on Emotions and Mathematics
Xolocotzin, U. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-802218-4.00001-7 · Cited by 16 · see citing works
Examining Student Effort on Help through Response Time Decomposition
Gurung, A., Botelho, A. F., & Heffernan, N. T. (2021) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3448139.3448167 · Cited by 15 · see citing works
Fu, W.-S., Zhang, J., Zhang, D., Li, T., Lan, M., & Liu, N. (2025) · Journal of Educational Computing Research · doi:10.1177/07356331241313126 · Cited by 15 · see citing works
Yu, H., Gupta, A., Lee, W., Arroyo, I., Betke, M., Allessio, D., Murray, T., Magee, J., & Woolf, B. P. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-77873-6_16 · Cited by 15 · see citing works
The Effects of Adaptive Feedback on Student’s Learning Gains
Bimba, A. T., Idris, N. B., Al-Hunaiyyan, A. A., Ibrahim, S. U., Mustafa, N., Supa'at, I., Zainal, N., & Ahmad, M. Y. (2021) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2021.0120709 · Cited by 14 · see citing works
A Systematic Review on Artificial Intelligence in Supporting Teaching Practice
Shi, L., & Choi, I. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780198882077.003.0015 · Cited by 18 · see citing works
Orji, F. A., & Vassileva, J. (2022) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2022.1015660 · Cited by 14 · see citing works
Oladele, J. I., Ndlovu, M., & Ayanwale, M. A. (2022) · Springer eBooks · doi:10.1007/978-3-031-13927-7_8 · Cited by 14 · see citing works
Guidance counselor reports of the ASSISTments college prediction model (ACPM)
Ocumpaugh, J. L., Baker, R. S., Pedro, M. O. C. Z. S., Hawn, M. A., Heffernan, C., Heffernan, N. T., & Slater, S. (2017) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3027385.3027435 · Cited by 14 · see citing works
A Classification Framework for Practice Exercises in Adaptive Learning Systems
Pelánek, R. (2020) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2020.3027050 · Cited by 13 · see citing works
Implementation of Motivational Tactics in Tutoring Systems: 20 years on
du Boulay, B., & Soldato, T. D. (2015) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-015-0052-1 · Cited by 13 · see citing works
Zhao, G., Li, M., Long, Z., & Fan, H. (2025) · Acta Psychologica · doi:10.1016/j.actpsy.2025.105558 · Cited by 20 · see citing works
Thi-Nga, H., Thi-Binh, V., & Nguyen, T. (2024) · Eurasia Journal of Mathematics Science and Technology Education · doi:10.29333/ejmste/14381 · Cited by 27 · see citing works
Pelánek, R., Effenberger, T., & Jarušek, P. (2024) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-024-09396-z · Cited by 19 · see citing works
Nowlan, N. S., Arya, A., Qorbani, H. S., & Abdinejad, M. (2023) · Computers & Education X Reality · doi:10.1016/j.cexr.2023.100012 · Cited by 12 · see citing works
Mosier, K. L., Fischer, U. M., Burian, B. K., & Kochan, J. A. (2017) · NASA STI Repository (National Aeronautics and Space Administration) · doi:10.13140/rg.2.2.25859.60966 · Cited by 12 · see citing works
The Effect of Assistance on Learning and Affect in an Algebra Tutor
Borracci, G., Gauthier, E., Jennings, J., Sale, K., & Müldner, K. (2019) · Journal of Educational Computing Research · doi:10.1177/0735633118822103 · Cited by 12 · see citing works
Modeling language learning using specialized Elo rating
Hou, J., Koppatz, M., Quecedo, J. M. H., Stoyanova, N., & Yangarber, R. (2019) · Workshop on Innovative Use of NLP for Building Educational Applications · doi:10.18653/v1/w19-4451 · Cited by 12 · see citing works
Leveraging Affect Transfer Learning for Behavior Prediction in an Intelligent Tutoring System
Ruiz, N., Yu, H., Allessio, D., Jalal, M., Joshi, A., Murray, T., Magee, J., Whitehill, J., Ablavsky, V., Arroyo, I., et al. (2021) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg52635.2021.9667001 · Cited by 12 · see citing works
Basham, J. D., Han, K., Zhang, L., & Yang, S. (2020) · Advancing inclusive and special education in the Asia-Pacific · doi:10.1007/978-981-15-4443-9_3 · Cited by 12 · see citing works
Personalized Learning for the Developing World
Zualkernan, I. A. (2015) · Lecture notes in educational technology · doi:10.1007/978-3-662-47724-3_13 · Cited by 12 · see citing works
Craig, S. D., Graesser, A. C., & Perez, R. S. (2018) · International Journal of STEM Education · doi:10.1186/s40594-018-0111-x · Cited by 12 · see citing works
Using Technology to Address Individual Differences in Learning
Antonenko, P. D., Dawson, K., Cheng, L., & Wang, J. (2020) · Springer eBooks · doi:10.1007/978-3-030-36119-8_6 · Cited by 10 · see citing works
- Authors
- Arroyo, I., Woolf, B. P., Burelson, W., Muldner, K., Rai, D., & Tai, M.
- Affiliations
- Worcester Polytechnic Institute (US)
- University of Massachusetts Amherst (US)
- New York University (US)
- Corresponding author
- Arroyo, Ivon
- Venue
- International Journal of Artificial Intelligence in Education
- Publisher
- Elsevier BV
- Published
- 2014-12
- Volume
- 24
- Issue
- 4
- Pages
- 387-426
- ISSN
- 1560-4292 (ISSN-L)
- OpenAlex
- W2094147479
- Cited by
- 263
- References
- 106
- Citations by year
- 2026: 13 · 2025: 36 · 2024: 25 · 2023: 36 · 2022: 31 · 2021: 22 · 2020: 22 · 2019: 18 · 2018: 17 · 2017: 19 · 2016: 11 · 2015: 12 · 2014: 1
- FWCI
- 14.29
- Type
- journal article
- Language
- en
- Update notices
- Open access
- hybrid
- doi.org
- Licence
- Locations
- International Journal of Artificial Intelligence in Education (publishedVersion, cc-by-nc-nd)
- Funders
- National Science Foundation (1324385)
- Office of Naval Research (N0001413C0127)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- adaptive tutoring systems, mathematics education, metacognition, student engagement, student motivation, personalized learning, emotion sensing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review