nach oben

Technology, Knowledge and Learning

Erschienen in:

29.08.2017 | Original research

Using a Recommendation System to Support Problem Solving and Case-Based Reasoning Retrieval

verfasst von: Andrew A. Tawfik, Hamed Alhoori, Charles Wayne Keene, Christian Bailey, Maureen Hogan

Erschienen in: Technology, Knowledge and Learning | Ausgabe 1/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

In case library learning environments, learners are presented with an array of narratives that can be used to guide their problem solving. However, according to theorists, learners struggle to identify and retrieve the optimal case to solve a new problem. Given the challenges novice face during case retrieval, recommender systems can be embedded in case libraries to support the decision-making process about which case is most relevant to solve new problems. This emerging technology reports how experts’ assessment of case relevancy was used to retrieve and suggest the most relevant cases for the learner as they engaged in an inquiry-based learning. Specifically, our case library learning system integrates a content-based filtering, which recommends items similar to those a user has selected based on item descriptions or other user data, and is most widely used in textual domains. Implications for practice are also discussed.

Vorheriger Artikel Factors Influencing Teachers’ Attitudes Toward Mobile Technology Integration in K-12

Nächster Artikel Ng Wan: New Digital Technology in Education: Conceptualizing Professional Learning for Educators

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Amatriain, X., Lathia, N., Pujol, J. M., Kwak, H., & Oliver, N. (2009). The wisdom of the few: A collaborative filtering approach based on expert opinions from the web. In Proceedings of the 32nd international ACM SIGIR conference on research and development in information retrieval (pp. 532–539). New York, NY, USA: ACM.

Balabanović, M., & Shoham, Y. (1997). Fab: Content-based, collaborative recommendation. Communications of the ACM, 40(3), 66–72.CrossRef

Belland, B. R., Walker, A. E., Kim, N. J., & Lefler, M. (2016). Synthesizing results from empirical research on computer-based scaffolding in STEM education. Review of Educational Research. doi:10.3102/0034654316670999.

Bousquet, O., & Bottou, L. (2008). The tradeoffs of large scale learning. In J. C. Platt, D. Koller, Y. Singer, & S. T. Roweis (Eds.), Advances in neural information processing systems 20 (pp. 161–168). Red Hook: Curran Associates, Inc.

Danish, J. A. (2014). Applying an activity theory lens to designing instruction for learning about the structure, behavior, and function of a honeybee system. Journal of the Learning Sciences, 23(2), 100–148.CrossRef

Ertmer, P., & Koehler, A. A. (2014). Online case-based discussions: Examining coverage of the afforded problem space. Educational Technology Research and Development, 62(5), 617–636.CrossRef

Fitzgerald, G., Mitchem, K., Hollingsead, C., Miller, K., Koury, K., & Tsai, H.-H. (2011). Exploring the bridge from multimedia cases to classrooms: Evidence of transfer. Journal of Special Education Technology, 26(2), 23–38.CrossRef

Gartmeier, M., Bauer, J., Fischer, M. R., Hoppe-Seyler, T., Karsten, G., Kiessling, C., et al. (2015). Fostering professional communication skills of future physicians and teachers: effects of e-learning with video cases and role-play. Instructional Science, 43(4), 443–462.CrossRef

Goldberg, D., Nichols, D., Oki, B. M., & Terry, D. (1992). Using collaborative filtering to weave an information tapestry. Communications of the ACM, 35(12), 61–70.CrossRef

Hernandez-Serrano, J., & Jonassen, D. H. (2003). The effects of case libraries on problem solving. Journal of Computer Assisted learning, 19(1), 103–114.CrossRef

Herrington, J., Reeves, T. C., & Oliver, R. (2014). Authentic learning environments. In J. M. Spector, M. D. Merrill, J. Elen, & M. J. Bishop (Eds.), Handbook of research on educational communications and technology (4th ed., pp. 453–464). New York, NY: Springer.

Hill, W., Stead, L., Rosenstein, M., & Furnas, G. (1995). Recommending and evaluating choices in a virtual community of use. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 194–201). New York, NY, USA: ACM Press/Addison-Wesley Publishing Co.

Hmelo-Silver, C. E., Marathe, S., & Liu, L. (2007). Fish swim, rocks sit, and lungs breathe: Expert-novice understanding of complex systems. Journal of the Learning Sciences, 16(3), 307–331.CrossRef

Hmelo-Silver, C. E., & Pfeffer, M. G. (2004). Comparing expert and novice understanding of a complex system from the perspective of structures, behaviors, and functions. Cognitive Science, 28(1), 127–138.CrossRef

Ifenthaler, D. (2017). Learning analytics design. In L. Lin & M. Spector (Eds.), The sciences of learning and instructional design: Constructive articulation between communities (pp. 202–211). New York, NY: Routledge.

Ifenthaler, D., Masduki, I., & Seel, N. M. (2011). The mystery of cognitive structure and how we can detect it: Tracking the development of cognitive structures over time. Instructional Science, 39(1), 41–61.CrossRef

Jacobson, M. J. (2001). Problem solving, cognition, and complex systems: Differences between experts and novices. Complexity, 6(3), 41–49.CrossRef

Jeong, H., & Hmelo-Silver, C. E. (2010). Productive use of learning resources in an online problem-based learning environment. Computers in Human Behavior, 26(1), 84–99.CrossRef

Jeong, H., & Hmelo-Silver, C. E. (2016). Seven affordances of computer-supported collaborative learning: How to support collaborative learning? How can technologies help? Educational Psychologist, 51(2), 247–265.CrossRef

Jonassen, D. H. (1997). Instructional design models for well-structured and ill-structured problem-solving learning outcomes. Educational Technology Research and Development, 45(1), 65–94.CrossRef

Jonassen, D. H. (2011). ASK systems: Interrogative access to multiple ways of thinking. Educational Technology Research and Development, 59(1), 159–175.CrossRef

Jonassen, D. H., & Hung, W. (2008). All problems are not equal: implications for problem-based learning. Interdisciplinary Journal of Problem-Based Learning, 2(2). Retrieved from http://docs.lib.purdue.edu/ijpbl/vol2/iss2/4.

Kim, H., & Hannafin, M. J. (2011). Developing situated knowledge about teaching with technology via web-enhanced case-based activity. Computers & Education, 57(1), 1378–1388.CrossRef

Kirschner, P., Sweller, J., & Clark, R. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86.CrossRef

Kolodner, J. (1991). Improving human decision making through case-based decision aiding. AI Magazine, 12(2), 52–68.

Kolodner, J. L., Owensby, J. N., & Guzdial, M. (2004). Case-based learning aids. In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology: A project of the Association for educational communications and technology (2nd ed., pp. 829–861). Mahwah, NJ: Lawrence Erlbaum Associates.

Konstan, J. A., Miller, B. N., Maltz, D., Herlocker, J. L., Gordon, L. R., & Riedl, J. (1997). GroupLens: Applying collaborative filtering to Usenet news. Communications of the ACM, 40(3), 77–87.CrossRef

Koren, Y., Bell, R., Volinsky, C., et al. (2009). Matrix factorization techniques for recommender systems. Computer, 42(8), 30–37.CrossRef

Lajoie, S. P., Hmelo-Silver, C. E., Wiseman, J. G., Chan, L. K., Lu, J., Khurana, C., et al. (2014). Using online digital tools and video to support international problem-based learning. Interdisciplinary Journal of Problem-Based Learning, 8(2), 6.CrossRef

Lazonder, A., & Harmsen, R. (2016). Meta-analysis of inquiry-based learning: Effects of guidance. Review of Educational Research, 87(4), 1–38.

Leary, H., & Walker, A. (2009). A problem based learning meta analysis: Differences across problem types, implementation types, disciplines, and assessment levels. Interdisciplinary Journal of Problem-Based Learning, 3(1). Retrieved from http://docs.lib.purdue.edu/ijpbl/vol3/iss1/3.

Loh, C. S., Sheng, Y., & Li, I.-H. (2015). Predicting expert–novice performance as serious games analytics with objective-oriented and navigational action sequences. Computers in Human Behavior, 49, 147–155.CrossRef

Ma, W., Adesope, O. O., Nesbit, J. C., & Liu, Q. (2014). Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of Educational Psychology, 106(4), 901.CrossRef

Pazzani, M. J., & Billsus, D. (2007). Content-based recommendation systems. In P. Brusilovsky, A. Kobsa, & W. Nejdl (Eds.), The adaptive web (pp. 325–341). Berlin: Springer.CrossRef

Reiser, B. (2004). Scaffolding complex learning: The mechanisms of structuring and problematizing student work. Journal of the Learning Sciences, 13(3), 273–304.CrossRef

Resnick, P., & Varian, H. R. (1997). Recommender systems. Communications of the ACM, 40(3), 56–58.CrossRef

Schafer, B., Frankowski, D., Herlocker, J., & Sen, S. (2007). Collaborative filtering recommender systems. In P. Brusilovsky, A. Kobsa, & W. Nejdl (Eds.), The adaptive web (pp. 291–324). Berlin: Springer.CrossRef

Schank, R. (1999). Dynamic memory revisited (2nd ed.). Cambridge, England: Cambridge University Press.CrossRef

Schein, A. I., Popescul, A., Ungar, L. H., & Pennock, D. M. (2002). Methods and metrics for cold-start recommendations. In Proceedings of the 25th annual international ACM SIGIR conference on research and development in information retrieval (pp. 253–260). New York, NY, USA: ACM.

Schenke, K., & Richland, L. E. (2017). Preservice teachers’ use of contrasting cases in mathematics instruction. Instructional Science, 45(3), 311–329.CrossRef

Schon, D. A. (1984). The reflective practitioner: How professionals think in action (1st ed.). New York: Basic Books.

Shardanand, U., & Maes, P. (1995). Social information filtering: Algorithms for automating “word of mouth.” In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 210–217). New York: ACM Press/Addison-Wesley Publishing Co.

Shokouhi, S. V., Skalle, P., & Aamodt, A. (2014). An overview of case-based reasoning applications in drilling engineering. Artificial Intelligence Review, 41(3), 317–329.CrossRef

Speier, C., Valacich, J. S., & Vessey, I. (1999). The influence of task interruption on individual decision making: an information overload perspective. Decision Sciences, 30(2), 337–360.CrossRef

Tawfik, A. A. (2017). Do cases teach themselves? A comparison of case library prompts in supporting problem-solving during argumentation. Journal of Computing in Higher Education, 29(2), 267–285.CrossRef

Tawfik, A. A., & Jonassen, D. H. (2013). The effects of successful versus failure-based cases on argumentation while solving decision-making problems. Educational Technology Research & Development, 61(3), 385–406.

Tawfik, A. A., & Kolodner, J. L. (2016). Systematizing scaffolding for problem-based learning: A view from case-based reasoning. Interdisciplinary Journal of Problem-Based Learning, 10(1), 6.

van Merriënboer, J. J. G. (2013). Perspectives on problem solving and instruction. Computers & Education, 64, 153–160.CrossRef

Vygotsky, L. S. (1978). Mind in society. Cambridge, MA: Harvard University Press.

Weinberger, A., & Fischer, F. (2006). A framework to analyze argumentative knowledge construction in computer-supported collaborative learning. Computers & Education, 46(1), 71–95.CrossRef

Woodruff, A., Gossweiler, R., Pitkow, J., Chi, E. H., & Card, S. K. (2000). Enhancing a digital book with a reading recommender. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 153–160). New York, NY, USA: ACM.

Xing, W., Guo, R., Petakovic, E., & Goggins, S. (2015). Participation-based student final performance prediction model through interpretable Genetic Programming: Integrating learning analytics, educational data mining and theory. Computers in Human Behavior, 47, 168–181.CrossRef

Titel: Using a Recommendation System to Support Problem Solving and Case-Based Reasoning Retrieval
verfasst von: Andrew A. Tawfik
Hamed Alhoori
Charles Wayne Keene
Christian Bailey
Maureen Hogan
Publikationsdatum: 29.08.2017
Verlag: Springer Netherlands
Erschienen in: Technology, Knowledge and Learning / Ausgabe 1/2018
Print ISSN: 2211-1662
Elektronische ISSN: 2211-1670
DOI: https://doi.org/10.1007/s10758-017-9335-y

Premium Partner

Marktübersichten

Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen.

Zur Marktübersicht

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 1/2018

Distributed Scaffolding: Synergy in Technology-Enhanced Learning Environments

Are We on Our Way to Becoming a “Helicopter University”? Academics’ Views on Learning Analytics

PBL Group Autonomy in a High School Environmental Science Class

Observing and Understanding an On-Line Learning Activity: A Model-Based Approach for Activity Indicator Engineering

The Temporal Attentive Observation (TAO) Scale: Development of an Instrument to Assess Attentive Behavior Sequences During Serious Gameplay

Ng Wan: New Digital Technology in Education: Conceptualizing Professional Learning for Educators

Premium Partner

Marktübersichten