Observing how a knowledgeable person demonstrates (or ‘models’) how to perform a task is a natural way of learning and can help with the acquisition of new skills (Van Gog & Rummel, 2010). Over the past years, video-based modeling examples have become easier to generate and disseminate. However, learners are often deprived from important social cues such as eye movements, head turns, or pointing gestures to the referred elements which would, in a traditional classroom setting, guide the learners’ attention to understand the model’s references (Ouwehand, van Gog, & Paas, 2015). One idea for fostering video learning is ‘Eye Movement Modelling Examples’ (Van Gog, Jarodzka, Scheiter, Gerjets, & Paas, 2009). In EMMEs, a model’s eye movements are superimposed onto the task material during execution, for instance as circles or a spotlight. These eye-movement displays could disambiguate the model’s references and thus improve the learners’ understanding. In the field of programming education, studies recently showed promising first results that EMME-based interventions can foster the acquisition of programming skills (Bednarik, Schulte, Budde, Heinemann, & Vrzakova, 2018; Stein & Brennan, 2004). However, clear design guidelines on how to create an optimal EMME are lacking and the creation process of EMMEs differs highly across studies. For instance, model instructions to create EMMEs range from no specific instruction (e.g., Litchfield, Ball, Donovan, Manning, & Crawford, 2010; Nalanagula, Greenstein, & Gramopadhye, 2006) to studies that explicitly prompt the models to adjust their behavior in a didactic manner to a novice audience (e.g., Jarodzka et al., 2012; Jarodzka, van Gog, Dorr, Scheiter, & Gerjets, 2013). Whether, and if so, to what extent, such instructions affect learning outcomes, is unknown. On the one hand, following naturally behaving experts might be more difficult for learners than following didactic examples. On the other hand, natural modeling examples could foster observational learning and the learners could gain insights into the standards their performance should ultimately meet. Our study aims at investigating how displaying either programming experts’ natural or didactic behavior in EMMEs affects learners’ mental effort ratings, video understanding, and debugging performance. This can later provide researchers and practitioners with evidence-based guidelines on how to create effective EMME videos and raise awareness of the importance of model instruction for EMME creation. Data collection will take place in May and June 2019 and we will present preliminary results at the network meeting. References Bednarik, R., Schulte, C., Budde, L., Heinemann, B., & Vrzakova, H. (2018). Eye-movement Modeling Examples in Source Code Comprehension: A Classroom Study. Paper presented at the Proceedings of the 18th Koli Calling International Conference on Computing Education Research. Jarodzka, H., Balslev, T., Holmqvist, K., Nyström, M., Scheiter, K., Gerjets, P., & Eika, B. (2012). Conveying clinical reasoning based on visual observation via eye-movement modelling examples. Instructional Science, 40(5), 813-827. Jarodzka, H., van Gog, T., Dorr, M., Scheiter, K., & Gerjets, P. (2013). Learning to see: Guiding students' attention via a model's eye movements fosters learning. Learning and Instruction, 25, 62-70. Litchfield, D., Ball, L. J., Donovan, T., Manning, D. J., & Crawford, T. (2010). Viewing another person's eye movements improves identification of pulmonary nodules in chest x-ray inspection. Journal of Experimental Psychology: Applied, 16(3), 251. Nalanagula, D., Greenstein, J. S., & Gramopadhye, A. K. (2006). Evaluation of the effect of feedforward training displays of search strategy on visual search performance. International Journal of Industrial Ergonomics, 36(4), 289-300. Ouwehand, K., van Gog, T., & Paas, F. (2015). Designing effective video-based modeling examples using gaze and gesture cues. Educational Technology & Society, 18(4), 78-88. Stein, R., & Brennan, S. E. (2004). Another person's eye gaze as a cue in solving programming problems. Paper presented at the Proceedings of the 6th international conference on Multimodal interfaces. Van Gog, T., Jarodzka, H., Scheiter, K., Gerjets, P., & Paas, F. (2009). Attention guidance during example study via the model’s eye movements. Computers in Human Behavior, 25(3), 785-791. Van Gog, T., & Rummel, N. (2010). Example-based learning: Integrating cognitive and social-cognitive research perspectives. Educational Psychology Review, 22(2), 155-174.
|Number of pages||2|
|Publication status||Published - Oct 2019|
|Event||Developing and stimulating competencies: Methodological challenges and opportunities for research: Networking event - The Leuven Institute for Ireland in Europe, Leuven, Belgium|
Duration: 16 Oct 2019 → 18 Oct 2019
|Conference||Developing and stimulating competencies: Methodological challenges and opportunities for research|
|Period||16/10/19 → 18/10/19|
Emhardt, S. N., Jarodzka, H. M., Drumm, C., Van Gog, T., & Brand - Gruwel, S. (2019). Effects of observing a model’s natural or didactic problem-solving behavior in eye movement modeling examples. 61-62. Poster session presented at Developing and stimulating competencies: Methodological challenges and opportunities for research, Leuven, Belgium. https://ppw.kuleuven.be/o_en_o/CIPenT/wog-2019/programme_book