PossibleTopics

The ASSISTmentsTestBed seeks experiments of all types.  Below we list 8 different thrust areas, as well as example studies that fall into those areas.  Below are  the citations.

Thrust

Researcher Name

Citation

L/W

Representative

Experiment Type

Study Prompts to Guide Learning

Dedre Gentner

Jee, Uttal, Gentner, et al. (2003)

L

Prompting for comparison of analogous problems and worked examples

 

Kathleen Arnold

Arnold & McDermott (2013)

W

Testing the value of free recall

 

Daniel Schacter

Szpunar, Khan & Schacter (2013)

L

Inserting quizzes and tests to maintain and guide students' focus

Feedback

Bethany Rittle-Johnson

Fyfe, Rittle-Johnson & DeCaro (2012)

L

Immediate versus delayed timing of feedback on problems

 

Tiffany Barnes

Stamper, Eagle, Barnes & Croy (2013)

L

Types of hints that are provided adaptively to learners

 

John Sweller

Sweller, Kirschner & Clark (2007)

W

Comparing levels of feedback from guided to open

 

Peter Khooshabeh

Keehner, Hegarty, Cohen, et al. (2008)

W

Comparing what you see versus the role of interacting

Sequencing & Spacing of Learning Activities

Henry Roediger

Roediger & Karpicke (2006)

L

Changing the schedules and procedures for having students practice & quiz

 

Lindsey Richland

Richland, Kornell & Kao (2009)

L

Testing effectiveness of pre-testing and problem-solving prior to instruction

 

Nicholas Cepeda

Pashler, Rohrer, Cepeda & Carpenter (2007)

W

Spacing

 

Andrew Butler

Butler & Roediger (2007)

W

Testing effects

Self-Regulated Learning & Metacognition

Joyce Ehrlinger

Ehrlinger & Shain (2014)

L

Testing interaction interventions to increase motivation and teach learning strategies

 

Daniel Belenky

Belenky & Nokes-Malach (2013)

W

How framing a task changes what students learn

 

Ido Roll

Roll, Holmes, Day & Bonn (2012)

L

Examine types of metacognitive scaffolding provided in problem solving

Social Context & Interaction

Candace Walkington

Walkington (2013)

L

Adapting instructional materials to students' personal & peer interests

 

Erin Walker

Walker, Rummel & Koedinger (2011)

L

Embedding software & dynamics for peer assistance and question asking

 

Ethan Brown

Mazzocco, Murphy, Brown, et al. (2013)

W

How judgments of confidence impact performance on early algebra

Assessment

Anna Rafferty

Rafferty & Griffiths (2014)

L

Varying computational model used to diagnose learner state and generate scaffolding policy

 

Ryan Baker

Ocumpagh, Baker, et al. (2014)

L

Different computational methods for assessing affective states

 

John Nestojko

Storm, Bjork, Bjork & Nestojko (2006 )

W

Forgetting

Motivation & Engagement

Sidney D'Mello

Kelly, et al. (2013a)

L

Embedding motivational and encouraging videos from teachers

 

Joseph Jay Williams

Williams (2013)

L

Incorporation of messages fostering the growth mindset

 

Matthew Bernaki

Bernacki, Byrnes & Cromley (2012)

W

Goal setting

 

Nadia Chernyak

Chernyak & Kushnir (2013)

W

The role of choice

Mathematics Education Focus

Martina Rau

Rau, Aleven, Rummel & Rohrbach (2012)

W

Comparing representational formats in supporting mathematics learning

 

Table B-1.2 For each different topic, we list 3-5 researchers that work in that space.  The “L” indicates the researcher has given us a letter of support (see Appendix D), while “W” indicates that they attended our Webinar.  This table lists the type of experiment that the researcher has expressed running within the TestBed, as well as a citation of the researcher’s comparable work.

References
  •  Attali, Y. & Powers, D. (2010). Immediate Feedback and Opportunity to Revise Answers: Application of a Graded Response IRT Model. Applied Psychological Measurement 35(6), 472-479.Retrieved August 5, 2014 from http://goo.gl/vwpFVs
  • Belenky, D.M. & Nokes-Malach, T.J. (2013). Mastery-approach goals and knowledge transfer: An investigation into the effects of task structure and framing instructions. Learning and Individual Differences. 25, 21-34.
  • Bernacki, M.L., Byrnes, J.P. & Cromley, J.G. (2012). The effects of achievement goals and self-regulated learning behaviors on reading comprehension in technology-enhanced learning environments. Contemporary Educational Psychology. 37 (2): 148-161.
  • Butler, A.C., & Roediger, H.L., III. (2007). Testing improves long-term retention in a simulated classroom setting. European Journal of Cognitive Psychology. 19, 514-527.
  • Chernyak, N., & Kushnir, T. (2013). Giving Preschoolers Choice Increases Sharing Behavior. Psychological Science. 24 (10): 1971-1979.
  • Ehrlinger, J. & Shain, E.A. (2014). How accuracy in students’ self perceptions relates to success in learning. In V.A. Benassi, C.E. Overson, & C.M. Hakala (Eds.). Applying science of learning in education: Infusing psychological science into the curriculum. Retrieved from the Society for the Teaching of Psychology web site: http://teachpsych.org/ebooks/asle2014/index.php.
  • Fyfe, E.R., Rittle-Johnson, B. & DeCaro, M.S. (2012). The effects of feedback during exploratory mathematics problem solving: Prior knowledge matters. Journal of Educational Psychology. 104, 1094-1108.
  • Jee, B., Uttal, D., Gentner, D., Manduca, C., Shipley, T. & Sageman, B. (2013). Finding faults:  analogical comparison supports spatial concept learning in geoscience. Cognitive Processing, 14(2), 175-187.
  • Keehner, M., Hegarty, M., Cohen, C., Khooshabeh, P. & Montello, D.R. (2008). Spatial reasoning with external visualizations: what matters is what you see, not whether you interact. Cognitive Science. 32, 1099-1132.
  • Kelly, K., Heffernan, N., D'Mello, S., Namias, J., & Strain, A. (2013a). Adding Teacher-Created Motivational Video to an ITS. In Boonthum-Denecke, Youngblood (Eds) Proceedings of the Twenty-Sixth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2013, St. Pete Beach, Florida. May 22-24, 2013. AAAI Press 2013. pp. 503-508. Retrieved on June 2, 2014, from http://goo.gl/cDEEqf
  • Mazzocco, M.M.M., Murphy, M.M., Brown, E.C., Rinne, L. & Herold, K.H. (2013). Persistent consequences of atypical early number concepts. Frontiers in Psychology. 4: 486.
  • Ocumpaugh, J., Baker, R., Gowda, S., Heffernan, N., Heffernan, C. (2014). Population validity for Educational Data Mining models: A case study in affect detection. British Journal of Educational Technology, 45 (3), 487-501 Retrieved on August 5, 2014 from http://goo.gl/V6AJbY
  • Pashler, H., Rohrer, D., Cepeda, N. & Carpenter, S.K. (2007). Enhancing learning and retarding forgetting: Choices and consequences. Psychonomic Bulletin & Review. 14 (2), 187-193.
  • Rafferty, A. N. and Griffiths, T. L. (2014). “Diagnosing Algebra Understanding via Bayesian Inverse Planning.” Proceedings of the 7th International Conference on Educational Data Mining (p. 351- 352). [extended abstract] [PDF]
  • Rau, M., Aleven, V., Rummel, N., & Rohrbach, S. (2012). Sense Making Alone Doesn't Do It: Fluency Matters Too! ITS Support for Robust Learning with Multiple Representations. In S. Cerri, W. Clancey, G. Papadourakis & K. Panourgia (Eds.), Intelligent Tutoring Systems (Vol. 7315, pp. 174-184). Berlin / Heidelberg: Springer.
  • Richland, L. E., Kornell, N., & Kao, L. S. (2009). The pretesting effect: Do unsuccessful retrieval attempts enhance learning? Journal of Experimental Psychology: Applied, 15(3), 243.
  • Roediger, H. L. & Karpicke, J. D. (2006). The power of testing memory: Basic research and implications for educational practice. Perspectives on Psychological Science, 1, 181-210. [PDF]
  • Roll, I., Holmes, N. G., Day, J., & Bonn, D. (2012). Evaluating metacognitive scaffolding in guided invention activities. Instructional Science, 40, 691-710. doi:10.1007/s11251-012-9208-7
  • Stamper, J., Eagle, M., Barnes, T. & Croy, M. (2013). Experimental Evaluation of Automatic Hint Generation for a Logic Tutor. Intl. Journal on AI in Education (IJAIED). Volume 22(1-2): 3-17.
  • Storm, B.C., Bjork, E.L., Bjork, R.A., & Nestojko, J.F. (2006). Is retrieval success a necessary condition for retrieval-induced forgetting? Psychonomic Bulletin & Review. 13: 1023-1027.
  • Sweller, J., Kirschner, P.A., Clark, R.E. (2007). Why Minimally Guided Teaching Techniques Do Not Work: A Reply to Commentaries. Educational Psychologist. 42(2), 115-121.
  • Szpunar, K.K., Khan, N.Y., Schacter, D.L. (2013). Interpolated memory tests reduce mind wandering and improve learning of online lectures. Proceedings of the National Academy of Sciences. 110(16): 6313 - 6317.
  • Walker, E., Rummel, N., & Koedinger, K. R. (2011). Designing automated adaptive support to improve student helping behaviors in a peer tutoring activity. International Journal of Computer-Supported Collaborative Learning, 6(2),279-306.
  • Walkington, C. (2013). Using learning technologies to personalize instruction to student interests: The impact of relevant contexts on performance and learning outcomes. Journal of Educational Psychology, 105(4), 932-945.
  • Williams, J.J. (2013). Improving Learning in MOOCs by Applying Cognitive Science. Paper presented at the International Conference on Artificial Intelligence in Education, Memphis, TN.
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