Adcock, AB, & Eck, RNV (2005). Reliability and factor structure of the attitude toward tutoring agent scale (attas). Journal of Interactive Learning Research, 16(2), 195.
Google Scholar
Aleven, V, & Koedinger, K (2002). An effective metacognitive strategy: learning by doing and explaining with a computer-based cognitive tutor. Cognitive Science, 26(2), 147–179.
Article
Google Scholar
Aleven, V, Ogan, A, Popescu, O (2004). Evaluating the effectiveness of a tutorial dialogue system for self-explanation. In Intelligent Tutoring Systems (ITS) 2004. Springer, New York, (pp. 443–454).
Google Scholar
Aleven, V, McLaren, BM, Sewall, J, Koedinger, KR (2009). A new paradigm for intelligent tutoring systems: example-tracing tutors. International Journal of Artificial Intelligence in Education, 19(2), 105–154.
Google Scholar
Atkinson, RK, Renkl, A, Merrill, MM (2003). Transitioning from studying examples to solving problems: effects of self-explanation prompts and fading worked-out steps. Journal of Educational Psychology, 95(4), 774.
Article
Google Scholar
Beck, JE, & Gong, Y (2013). Wheel-spinning: students who fail to master a skill. In International Conference on Artificial Intelligence in Education. Springer, Heidelberg, (pp. 431–440).
Chapter
Google Scholar
Blackwell, LS, Trzesniewski, KH, Dweck, CS (2007). Implicit theories of intelligence predict achievement across an adolescent transition: a longitudinal study and an intervention. Child Development, 78(1), 246–263.
Article
Google Scholar
Bloom, BS. (1956). Taxonomy of educational objectives: the classification of educational goals. Harlow: Longman Group.
Google Scholar
Chi, M, & VanLehn, K (2010). Meta-cognitive strategy instruction in intelligent tutoring systems: how, when, and why. Educational Technology and Society, 13(1), 25–39.
Google Scholar
Chi, MT (2009). Active-constructive-interactive: a conceptual framework for differentiating learning activities. Topics in Cognitive Science, 1(1), 73–105.
Article
Google Scholar
Craig, SD, Driscoll, DM, Gholson, B (2004). Constructing knowledge from dialog in an intelligent tutoring system: interactive learning, vicarious learning, and pedagogical agents. Journal of Educational Multimedia and Hypermedia, 13(2), 163.
Google Scholar
Craig, SD, Hu, X, Graesser, AC, Bargagliotti, AE, Sterbinsky, A, Cheney, KR, Okwumabua, T (2013). The impact of a technology-based mathematics after-school program using aleks on student’s knowledge and behaviors. Computers & Education, 68, 495–504.
Article
Google Scholar
Epstein, J (2014). Basic skills diagnostic test. www.flaguide.org/tools/diagnostic/basic_skills_diagnostic.php. Accessed 15 June 2014.
Falmagne, JC, Albert, D, Doble, C, Eppstein, D, Hu, X, (Eds.) (2013). Knowledge spaces. Berlin, Germany: Springer.
Book
Google Scholar
Graesser, AC, Langston, MC, Lang, KL (1992). Designing educational software around questioning. Journal of Interactive Learning Research, 3(2), 235.
Google Scholar
Graesser, AC, D’Mello, SK, Hu, X, Cai, Z, Olney, A, Morgan, B (2012). AutoTutor. In: McCarthy, PM, & Boonthum, C (Eds.) In Applied natural language processing and content analysis: identification, investigation and resolution. IGI Global, Hershey, PA, (pp. 169–187).
Chapter
Google Scholar
Heidig, S, & Clarebout, G (2011). Do pedagogical agents make a difference to student motivation and learning. Educational Research Review, 6(1), 27–54.
Article
Google Scholar
Huang, X, Craig, SD, Xie, J, Graesser, A, Hu, X (2016). Intelligent tutoring systems work as a math gap reducer in 6th grade after-school program. Learning and Individual Differences, 47, 258–265.
Article
Google Scholar
Kulik, JA, & Fletcher, J (2016). Effectiveness of intelligent tutoring systems: a meta-analytic review. Review of Educational Research, 86(1), 42–78.
Article
Google Scholar
Landauer, TK, Foltz, PW, Laham, D (1998). An introduction to latent semantic analysis. Discourse Processes, 25(2-3), 259–284.
Article
Google Scholar
Lehman, B, D’Mello, S, Graesser, A (2012). Interventions to regulate confusion during learning. In Proceedings of the 11th international conference on Intelligent Tutoring Systems. Springer-Verlag, Berlin, Heidelberg, ITS’12, (pp. 576–578).
Chapter
Google Scholar
Nye, BD (2016). Its, the end of the world as we know it: transitioning aied into a service-oriented ecosystem. International Journal of Artificial Intelligence in Education, 26(2), 756–770.
Article
Google Scholar
Nye, BD, Graesser, AC, Hu, X (2013). Multimedia learning in intelligent tutoring systems. In: Mayer, RE (Ed.) In Multimedia Learning. 3rd Ed. Cambridge University Press, New York.
Google Scholar
Nye, BD, Graesser, AC, Hu, X (2014a). AutoTutor and family: a review of 17 years of science and math tutoring. International Journal of Artificial Intelligence in Education, 24(4), 427–469.
Article
Google Scholar
Nye, BD, Graesser, AC, Hu, X, Cai, Z (2014b). AutoTutor in the cloud: a service-oriented paradigm for an interoperable natural-language its. Journal of Advanced Distributed Learning Technology, 2(6), 35–48.
Google Scholar
Pane, JF, Griffin, BA, McCaffrey, DF, Karam, R (2014). Effectiveness of cognitive tutor algebra i at scale. Educational Evaluation and Policy Analysis, 36(2), 127–144.
Article
Google Scholar
Pintrich, PR, Smith, DA, García, T, McKeachie, WJ (1993). Reliability and predictive validity of the motivated strategies for learning questionnaire (mslq). Educational and Psychological Measurement, 53(3), 801–813.
Article
Google Scholar
Renkl, A (2005). The worked-out-example principle in multimedia learning. In: Mayer, RE (Ed.) In The Cambridge handbook of multimedia learning. Cambridge University Press, New York, (pp. 229–245).
Chapter
Google Scholar
Roschelle, J, & Kaput, J (1996). Educational software architecture and systemic impact: the promise of component software. Journal of Educational Computing Research, 14(3), 217–228.
Article
Google Scholar
Sabo, KE, Atkinson, RK, Barrus, AL, Joseph, SS, Perez, RS (2013). Searching for the two sigma advantage: evaluating algebra intelligent tutors. Computers in Human Behavior, 29(4), 1833–1840.
Article
Google Scholar
Schommer-Aikins, M, Duell, OK, Hutter, R (2005). Epistemological beliefs, mathematical problem-solving beliefs, and academic performance of middle school students. The Elementary School Journal, 105(3), 289–304.
Article
Google Scholar
Schroeder, NL, Adesope, OO, Gilbert, RB (2013). How effective are pedagogical agents for learning? A meta-analytic review. Journal of Educational Computing Research, 49(1), 1–39.
Article
Google Scholar
Schwonke, R, Renkl, A, Krieg, C, Wittwer, J, Aleven, V, Salden, R (2009). The worked-example effect: not an artefact of lousy control conditions. Computers in Human Behavior, 25(2, SI), 258–266.
Article
Google Scholar
Schworm, S, & Renkl, A (2007). Learning argumentation skills through the use of prompts for self-explaining examples. Journal of Educational Psychology, 99(2), 285.
Article
Google Scholar
Sullins, J, Meister, R, Craig, S, Wilson, W, Bargagliotti, A, Hu, X (2013). Is there a relationship between interacting with a mathematical intelligent tutoring system and students performance on standardized high-stake tests. Knowledge Spaces: Applications to education, 69–78.
VanLehn, K (2006). The behavior of tutoring systems. International Journal of Artificial Intelligence in Education, 16(3), 227–265.
Google Scholar
VanLehn, K (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197–221.
Article
Google Scholar
VanLehn, K, Siler, S, Murray, C, Yamauchi, T, Baggett, WB (2003). Why do only some events cause learning during human tutoring?Cognition and Instruction, 21(3), 209–249.
Article
Google Scholar
Vanlehn, K, Graesser, AC, Jackson, GT, Jordan, P, Olney, A, Rosé, CP (2007). When are tutorial dialogues more effective than reading?Cognitive Science, 31(1), 3–62. http://www.ncbi.nlm.nih.gov/pubmed/21635287.
Article
Google Scholar
Venkatesh, V, Morris, MG, Davis, GB, Davis, FD (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425–478.
Article
Google Scholar
Willingham, DT. (2009). Why don’t students like school?: a cognitive scientist answers questions about how the mind works and what it means for the classroom. San Francisco: Wiley.
Google Scholar