Acuña, S. R., García-Rodicio, H., & Sánchez, E. (2010). Fostering active processing of instructional explanations of learners with high and low prior knowledge. European Journal of Psychology of Education, 26
(4), 435–452.CrossRefGoogle Scholar
Anderson, J. (1983). The architecture of cognition
. Cambridge: Harvard University Press.Google Scholar
*Belenky, D. M., & Nokes-Malach, T. J. (2012). Motivation and transfer: the role of mastery-approach goals in preparation for future learning. Journal of the Learning Sciences, 21(3), 399-432.
Barnett, S. M., & Ceci, S. J. (2002). When and where do we apply what we learn? A taxonomy for far transfer. Psychological Bulletin, 128
(4), 612–637.CrossRefGoogle Scholar
Booth, J. L., Lange, K. E., Koedinger, K. R., & Newton, K. J. (2013). Using example problems to improve student learning in algebra: differentiating between correct and incorrect examples. Learning and Instruction, 25
, 24–34.CrossRefGoogle Scholar
Chi, M. T. H. (2000). Self-explaining expository texts: the dual processes of generating inferences and repairing mental models. In R. Glaser (Ed.), Advances in instructional psychology
(pp. 161–238). Hillsdale: Lawrence Erlbaum Associates.Google Scholar
Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5
(2), 121–152.CrossRefGoogle Scholar
Chi, M. T. H., Slotta, J. D., & de Leeuw, N. (1994). From things to processes: a theory of conceptual change for learning science concepts. Learning and Instruction, 4
, 27–43.CrossRefGoogle Scholar
DeCaro, D. A., DeCaro, M. S., & Rittle-Johnson, B. (2015). Achievement motivation and knowledge development during exploratory learning. Learning and Individual Differences, 37, 13–26.
*DeCaro, M. S., & Rittle-Johnson, B. (2012). Exploring mathematics problems prepares children to learn from instruction. Journal of Experimental Child Psychology, 113, 552-568
diSessa, A. A., Hammer, D., Sherin, B. L., & Kolpakowski, T. (1991). Inventing graphing: meta-representational expertise in children. The Journal of Mathematical Behavior, 10
(2), 117–160.Google Scholar
Duncker, K. (1945). On problem-solving. Psychological Monographs, 58(Whole No. 270).
Durkin, K., & Rittle-Johnson, B. (2012). The effectiveness of using incorrect examples to support learning about decimal magnitude. Learning and Instruction, 22
(3), 206–214.CrossRefGoogle Scholar
Eva, K. W., & Regehr, G. (2011). Exploring the divergence between self-assessment and self-monitoring. Advances in Health Sciences Education, 16
(3), 311–329.CrossRefGoogle Scholar
*Fyfe, E. R., DeCaro, M. S. & Rittle-Johnson, B. (2014). An alternative time for telling: when conceptual instruction prior to problem solving improves mathematical knowledge. British Journal of Educational Psychology, 84(3), 502-519.
*Glogger-Frey, I., Fleischer, C., Grüny, L., Kappich, J., & Renkl, A. (2015). Inventing a solution and studying a worked solution prepare differently for learning from direct instruction. Learning and Instruction, 39, 72-87.
Heckler, A. F., Kaminski, J. A., & Sloutsky, V. M. (2008). Learning associations that run counter to biases in learning: overcoming overshadowing and learned inattention. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. (pp. 511-516). Austin, TX: Cognitive Science Society
Holmes, N. G., Day, J., Park, A. H., Bonn, D. A., & Roll, I. (2014). Making the failure more productive: scaffolding the invention process to improve inquiry behaviours and outcomes in productive failure activities. Instructional Science, 42
(4), 523–538.CrossRefGoogle Scholar
*Hsu, C.-Y., Kalyuga, S. & Sweller, J. (2015). When should guidance be presented in physics instruction? Archives of Scientific Psychology, 3(1), 37-53.
Kalyuga, S., & Singh, A.-M. (2015). Rethinking the boundaries of cognitive load theory in complex learning. Educational Psychology Review. Advance Online Publication
*Kapur, M. (2010). Productive failure in mathematical problem solving. Instructional Science, 38(6), 523-550.
*Kapur, M. (2011). A further study of productive failure in mathematical problem solving: unpacking the design components. Instructional Science, 39(4), 561-579.
*Kapur, M. (2012). Productive failure in learning the concept of variance. Instructional Science, 40(4), 651-672.
Kapur, M. (2014). Comparing learning from productive failure and vicarious failure. Journal of the Learning Sciences, 23
(4), 651–677.CrossRefGoogle Scholar
*Kapur, M. (2014b). Productive failure in learning math. Cognitive Science, 38(5), 1008-1022.
Kapur, M. (2016). Examining productive failure, productive success, unproductive failure, and unproductive success in learning. Educational Psychologist, 51
(2), 289–299.CrossRefGoogle Scholar
*Kapur, M., & Bielaczyc, K. (2011). Classroom-based experiments in productive failure. In L. Carlson, C. Hoelscher, & T. F. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 2812–2817). Austin, TX: Cognitive Science Society.
*Kapur, M., & Bielaczyc, K. (2012). Designing for productive failure. The Journal of the Learning Sciences, 21(1), 45-83.
Koedinger, K. R., Corbett, A. T., & Perfetti, C. (2012). The knowledge-learning-instruction (KLI) framework: bridging the science-practice chasm to enhance robust student learning. Cognitive Science, 36
, 757–798.CrossRefGoogle Scholar
Leppink, J., Paas, F., Van Gog, T., Van der Vleuten, C., & Van Merrienboer, J. (2014). Effects of pairs of problems and examples on task performance and different types of cognitive load. Learning and Instruction, 30
, 32–42.CrossRefGoogle Scholar
Linn, M. C. (1995). Designing computer learning environments for engineering and computer science: the scaffolded knowledge integration framework. Journal of Science Education and Technology, 4
, 103–126.CrossRefGoogle Scholar
*Loehr, A. M., Fyfe, E. R., & Rittle-Johnson, B. (2014). Wait for it … delaying instruction improves mathematics problem solving: a classroom study. Journal of Problem Solving, 7(1), 36-49.
*Loibl, K. & Rummel, N. (2014a). Knowing what you don’t know makes failure productive. Learning and Instruction, 34, 74-85.
*Loibl, K., & Rummel, N. (2014b). The impact of guidance during problem-solving prior to instruction on students’ inventions and learning outcomes. Instructional Science, 42(3), 305-326.
*Matlen, B. J., & Klahr, D. (2013). Sequential effects of high and low instructional guidance on children’s acquisition of experimentation skills: is it all in the timing? Instructional Science, 41(3), 621-634.
Mazziotti, C., Loibl, K., & Rummel, N. (2014). Does collaboration affect learning in a productive failure setting? In: J. L. Polman, E. A. Kyza, D. K. O’Neill, I. Tabak, W. R. Penuel, A. S. Ju-row, K. O’Connor, T. Lee, T., & L. D’Amico, Proceedings of the 11th international conference of the learning sciences (ICLS 2014), Vol. 3 (pp. 1184-1185). International Society of the Learning Sciences, Inc.
Mazziotti, C., Loibl, K., & Rummel, N. (2015). Collaborative or individual learning within productive failure. Does the social form of learning make a difference? In O. Lindwall, P. Häkkinen, T. Koschman, P. Tchounikine, & S. Ludvigsen (Eds.), Exploring the material conditions of learning: the Computer Supported Collaborative Learning (CSCL) Conference 2015
(Vol. 2, pp. 570–575). Gothenburg: ISLS.Google Scholar
Nathan, M. J. (1998). Knowledge and situational feedback in a learning environment for algebra story problem solving. Interactive Learning Environments, 5
(1), 135–159.CrossRefGoogle Scholar
Nathan, M. J., Alibali, M. W., Masarik, D. K., Stephens, A. C., & Koedinger, K. R. (2010). Enhancing middle school students’ representational fluency: a classroom-based study. WCER Working Paper Series no, 2010-9
. Wisconsin Center for Educational Research: Madison, WI. Retrieved June 28, 2013, from http://www.wcer.wisc.edu/Publications/workingPapers/Working_Paper_No_2010_09.pdf
Needham, D. R., & Begg, I. M. (1991). Problem-oriented training promotes spontaneous analogical transfer: memory-oriented training promotes memory for training. Memory & Cognition, 19
(6), 543–57.CrossRefGoogle Scholar
Paul, A. M. (2012) Why floundering is good. Time Magazine
. Retrieved June 28, 2013, from http://ideas.time.com/2012/04/25/why-floundering-is-good/
Prediger, S. (2008). The relevance of didactic categories for analysing obstacles in conceptual change: revisiting the case of multiplication of fractions. Learning and Instruction, 18
(1), 3–17.CrossRefGoogle Scholar
Quilici, J. L., & Mayer, R. E. (1996). Role of examples in how students learn to categorize statistics word problems. Journal of Educational Psychology, 88
(1), 144–161.CrossRefGoogle Scholar
Quilici, J. L., & Mayer, R. E. (2002). Teaching students to recognize structural similarities between statistics word problems. Applied Cognitive Psychology, 16
(3), 325–342.CrossRefGoogle Scholar
Reisslein, J., Atkinson, R., Seeling, P., & Reisslein, M. (2006). Encountering the expertise reversal effect with a computer-based environment on electrical circuit analysis. Learning and Instruction, 16
, 92–103.CrossRefGoogle Scholar
Renkl, A. (2005). The worked-out-example principle in multimedia learning. In R. Mayer (Ed.), Cambridge handbook of multimedia learning
(pp. 229–246). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Renkl, A. (2014). Towards an instructionally-oriented theory of example-based learning. Cognitive Science, 38
, 1–37.CrossRefGoogle Scholar
Rittle-Johnson, B., & Schneider, M. (2014). Developing conceptual and procedural knowledge of mathematics. In R. Cohen Kadosh & A. Dowker (Eds.), Oxford handbook of numerical cognition
. Oxford: Oxford University Press.Google Scholar
Rittle-Johnson, B., & Star, J. R. (2009). Compared with what? The effects of different comparisons on conceptual knowledge and procedural flexibility for equation solving. Journal of Educational Psychology, 101
(3), 529–544.CrossRefGoogle Scholar
*Roll, I., Aleven, V., & Koedinger, K. R. (2009). Helping students know ‘further’—increasing the flexibility of students’ knowledge using symbolic invention tasks. In N.A. Taatgen & H. van Rijn (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp. 1169-1174). Austin: Cognitive Science Society.
*Roll, I., Aleven, V., & Koedinger, K. R. (2011). Outcomes and mechanisms of transfer. In L. Carlson, C. Hölscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 2824–2829). Austin: Cognitive Science Society.
Roll, I., Holmes, N. G., Day, J., & Bonn, D. (2012). Evaluating metacognitive scaffolding in guided invention activities. Instructional Science, 40
(4), 691–710.CrossRefGoogle Scholar
Roll, I., Wiese, E., Long, Y., Aleven, V., & Koedinger, K. R. (2014). Tutoring self- and co-regulation with intelligent tutoring systems to help students acquire better learning skills. In R. Sottilare, A. Graesser, X. Hu, & B. Goldberg (Eds.), Design recommendations for adaptive intelligent tutoring systems: volume 2—adaptive instructional strategies
(pp. 169–182). Orlando: U.S. Army Research Laboratory.Google Scholar
Sánchez, E., García Rodicio, H., & Acuña, S. R. (2009). Are instructional explanations more effective in the context of an impasse? Instructional Science, 37
(6), 537–563.CrossRefGoogle Scholar
Schmidt, H. G., De Volder, M. L., De Grave, W. S., Moust, J. H. C., & Patel, V. L. (1989). Exploratory models in the processing of science texts: the role of prior knowledge activation through small-group discussion. Journal of Educational Psychology, 81
(4), 610–619.CrossRefGoogle Scholar
*Schwartz, D. L., & Bransford, J. D. (1998). A time for telling. Cognition and Instruction, 16(4), 475–522.
*Schwartz, D. L., Chase, C. C., Oppezzo, M. A., & Chin, D. B. (2011). Practicing versus inventing with contrasting cases: the effects of telling first on learning and transfer. Journal of Educational Psychology, 103(4), 759–775.
*Schwartz, D. L., & Martin, T. (2004). Inventing to prepare for future learning: the hidden efficiency of encouraging original student production in statistics instruction. Cognition and Instruction, 22(2), 129–184.
Schwartz, D. L., Sears, D., & Chang, J. (2007). Reconsidering prior knowledge. In M. C. Lovett & P. Shah (Eds.), Thinking with data
(pp. 319–344). New York: Routledge.Google Scholar
Sears, D. A. (2006). Effects of innovation versus efficiency tasks on collaboration and learning
. Doctoral dissertation, Stanford University, California. Retrieved November 07, 2012, from http://www.stat.auckland.ac.nz/~iase/publications/dissertations/06.Sears.Dissertation.pdf
Siegler, R. S. (1983). How knowledge influences learning. American Scientist, 71
, 631–638.Google Scholar
Sweller, J. (1988). Cognitive load during problem solving: effects on learning. Cognitive Science, 12
(2), 257–285.CrossRefGoogle Scholar
Sweller, J., van Merrienboer, J., & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10
(3), 251–296.CrossRefGoogle Scholar
Toth, E. E., Klahr, D., & Chen, Z. (2000). Bridging research and practice: a cognitively-based classroom intervention for teaching experimentation skills to elementary school children. Cognition and Instruction, 18
(4), 423–459.CrossRefGoogle Scholar
Van Gog, T., Kester, L., & Paas, F. (2011). Effects of worked examples, example-problem, and problem example pairs on novices’ learning. Contemporary Educational Psychology, 36
, 212–218.CrossRefGoogle Scholar
Van Gog, T., & Rummel, N. (2010). Example-based learning: integrating cognitive and social-cognitive research perspectives. Educational Psychology Review, 22
(2), 155–174.CrossRefGoogle Scholar
VanLehn, K. (1999). Rule learning events in the acquisition of a complex skill: an evaluation of cascade. The Journal of the Learning Sciences, 8
(1), 71–125.CrossRefGoogle Scholar
VanLehn, K., Siler, S., Murray, C., Yamauchi, T., & Baggett, W. B. (2003). Why do only some events cause learning during human tutoring? Cognition and Instruction, 21
(3), 209–249.CrossRefGoogle Scholar
Vosniadou, S., & Verschaffel, L. (2004). Extending the conceptual change approach to mathematics learning and teaching. Learning and Instruction, 14
(5), 445–451.CrossRefGoogle Scholar
Wertheimer, M. (1959). Productive thinking
. New York: Harper & Row.Google Scholar
Westermann, K., & Rummel, N. (2012). Delaying instruction: evidence from a study in a university relearning setting. Instructional Science, 40
(4), 673–689.CrossRefGoogle Scholar
Wiedmann, M., Leach, R. C., Rummel, N., & Wiley, J. (2012). Does group composition affect learning by invention? Instructional Science, 40
(4), 711–730.CrossRefGoogle Scholar