ADAPTIVE COGNITIVE TUTORS USING MACHINE LEARNING
How does the sequencing of pedagogical activities impact student learning? Answers to this question can both contribute to core learning sciences knowledge, as well as have important practical implications for how educational activities should be sequenced in order to maximize learning. As such, there has been significant interest in this issue, and prior research suggests that student learning can be quite sensitive to temporal sequencing.
Collaborative and individual learning appear to have complementary strengths; however, the best way to combine these learning methods is still unclear. While previous work has demonstrated the effectiveness of Intelligent Tutoring Systems (ITSs) for individual learning, collaborative learning with ITSs is much less frequent–especially for young
This project investigates how crowdsourcing and social media can spur innovation in the classroom. Crowd-based technologies have the potential to change design education by providing a socio-technical infrastructure that enables frequent and valuable interactions with stakeholders. We seek to understand how crowdsourcing and social media can affect student learning and motivation in the classroom. While online crowds can potentially provide diverse, scalable, and quick feedback, this input can also be noisy and ambiguous. To explore these technologies, we created a set of simple classroom activities to demonstrate how and why students can use online crowds for need finding, ideating, prototyping, and pitching.
ENGAGE: INSPIRING THE NEXT GENERATION OF SCIENTISTS THROUGH GAMES
The ENGAGE program seeks to develop interactive game-based technologies for pre-k through grade three students to inspire them to become future innovators by educating them in STEM skills. To get the target audience to play, these games must meet the highest standards for quality and entertainment. The goal is to create games that improve over time by analyzing play across a large population of anonymous users. As a result, ENGAGE hopes to not only produce valuable game-based teaching tools but to also provide insights into teaching techniques that can be applied to future products and classroom STEM learning.
Aleven, V., McLaughlin, E. A., Glenn, R. A., Koedinger, K. R. (2017). Instruction Based on Adaptive Learning Technologies. In Mayer, R. E., & Alexander, P. A. (Eds.). Handbook of research on learning and instruction (2nd ed.). Routledge.
Hui, J., Jue, R., Glenn, A., Gerber, E., Dow, S. Using Anonymity and Communal Efforts to Improve Quality of Crowdsourced Feedback. in Proceedings of Human Computation and Crowdsourcing, AAAI Press, 2015
Glenn, A. (2015). The relationships of word processing in academic work and student achievement scores on the national assessment of educational progress (Doctoral dissertation, DUQUESNE UNIVERSITY).
Aleven, V., Dow, S., Christel, M., Stevens, S., Rosé, C., Koedinger, K., … & Zhang, X., (2013). Supporting social-emotional development in collaborative inquiry games for K-3 science learning. Games+Learning+Society Conference 9.0
Christel, M., Stevens, S., Champer, M., Balash, J., Brice, S., Maher, B., … & Harpstead, E. (2013, September). Beanstalk: A unity game addressing balance principles, socio-emotional learning and scientific inquiry. In Proc. Int’l Games Innovation Conf. IEEE, NY (pp. 36-39).
THE RELATIONSHIPS OF WORD PROCESSING IN ACADEMIC WORK AND STUDENT ACHIEVEMENT SCORES ON THE NATIONAL ASSESSMENT OF EDUCATIONAL PROGRESS
This study is a secondary analysis of the 2011 NAEP writing test investigating the relationships between word processing in academic work and achievement test scores. Using data and methods to overcome several of the limitations found in research surrounding instructional technology, the statistical analyses constructed a table of z– scores and p-values that describe the relationship between both general use and specific uses of word processors and the total score on the NAEP writing assessment. Heuristic analysis of this table finds that there is a persistent and positive relationship between the use of word processors and writing achievement score. Specifically, the use of the backspace key, using word processors to make changes to a paper, using word processors to complete writing started by hand, and using the thesaurus function included in word processors are strongly related to achievement score. Further, the interactions of composition, editing, and revision are more complex that previously thought and may be growing as students comfortable with a new generation of technology continue to break the paradigm of the writing process. Finally, this study explores a new relationship between small edits and measuring the quality of writing by suggesting that word processors make the purpose of edits more important that simply the size of the edit.