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Learning from Videos Showing a Dialog Fosters More Positive Affect Than Learning from a Monolog

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Artificial Intelligence in Education (AIED 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11626))

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Abstract

How much students learn from instructional videos is influenced by the type of video. Prior work has shown that when students are given a video showing a dialog between a tutor and a tutee, they learn more than if the video shows a monolog delivered by a tutor. To date, however, there does not exist work investigating how each type of video impacts student affect. To fill this gap, we apply sentiment analysis to transcripts of students learning in each context. We show that learning from videos with dialog fosters more positive affect for university-level students, but not for middle-school students.

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References

  1. Arroyo, I., Woolf, B., Burleson, W., Muldner, K., Rai, D., Tai, M.: A multimedia adaptive tutoring system for mathematics that addresses cognition, metacognition and affect. Int. J. Artif. Intell. Educ. 24(4), 387 (2014)

    Google Scholar 

  2. Baker, R.S., D’Mello, S.K., Rodrigo, M.M.T., Graesser, A.C.: Better to be frustrated than bored: the incidence, persistence, and impact of learners’ cognitive-affective states during interactions with three different computer-based learning environments. Int. J. Hum Comput Stud. 68(4), 223–241 (2010)

    Article  Google Scholar 

  3. Chi, M.T., Kang, S., Yaghmourian, D.L.: Why students learn more from dialogue-than monologue-videos: analyses of peer interactions. J. Learn. Sci. 26(1), 10–50 (2017)

    Article  Google Scholar 

  4. Craig, S.D., Chi, M.T., VanLehn, K.: Improving classroom learning by collaboratively observing human tutoring videos while problem solving. J. Educ. Psychol. 101(4), 779–789 (2009)

    Article  Google Scholar 

  5. Craig, S.D., Gholson, B., Brittingham, J.K., Williams, J.L., Shubeck, K.T.: Promoting vicarious learning of physics using deep questions with explanations. Comput. Educ. 58(4), 1042–1048 (2012)

    Article  Google Scholar 

  6. Craig, S., Driscoll, D., Gholson, B.: Constructing knowledge from dialog in an intelligent tutoring system: interactive learning, vicarious learning, and pedagogical agents. J. Educ. Multimed. Hypermedia 13(2), 163–183 (2004)

    Google Scholar 

  7. Crossley, S., Kyle, K., McNamara, D.: Sentiment analysis and social cognition engine (SEANCE): an automatic tool for sentiment, social cognition, and social order analysis. Behav. Res. Methods 49(3), 803 (2017)

    Google Scholar 

  8. D’Mello, S., Graesser, A.: Autotutor and affective autotutor. ACM Trans. Interact. Intell. Syst. 2(4), 1–39 (2012)

    Article  Google Scholar 

  9. D’Mello, S., Lehman, B., Pekrun, R., Graesser, A.: Confusion can be beneficial for learning. Learn. Instr. 29, 153–170 (2014)

    Article  Google Scholar 

  10. Gholson, B., Craig, S.D.: Promoting constructive activities that support vicarious learning during computer-based instruction. Educ. Psychol. Rev. 18(2), 119–139 (2006)

    Article  Google Scholar 

  11. Kizilcec, R.: Showing face in video instruction: effects on information retention, visual attention, and affect. In: SIGCHI Conference on Human Factors in Computing Systems (CHI), pp. 2095–2102 (2014)

    Google Scholar 

  12. Muldner, K., Lam, R., Chi, M.T.H.: Comparing learning from observing and from human tutoring. J. Educ. Psychol. 106(1), 69–85 (2014)

    Article  Google Scholar 

  13. Muller, D.A., Bewes, J., Sharma, M.D., Reimann, P.: Saying the wrong thing: improving learning with multimedia by including misconceptions. J. Comput. Assist. Learn. 24(2), 144–155 (2008)

    Article  Google Scholar 

  14. Muller, D.A., Sharma, M.D., Eklund, J., Reimann, P.: Conceptual change through vicarious learning in an authentic physics setting. Instr. Sci. 35(6), 519–533 (2007)

    Article  Google Scholar 

  15. Newman, H., Joyner, D.: Sentiment analysis of student evaluations of teaching. In: Penstein Rosé, C., et al. (eds.) AIED 2018. LNCS (LNAI), vol. 10948, pp. 246–250. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93846-2_45

    Chapter  Google Scholar 

  16. Pekrun, R., Goetz, T., Titz, W., Perry, R.P.: Academic emotions in students’ self- regulated learning and achievement: a program of qualitative and quantitative research. Educ. Psychol. 37(2), 91–105 (2002)

    Article  Google Scholar 

  17. Putwain, D.W., Becker, S., Symes, W., Pekrun, R.: Reciprocal relations between students’ academic enjoyment, boredom, and achievement over time. Learn. Instr. 54, 73–81 (2018)

    Article  Google Scholar 

  18. Van Gog, T., Verveer, I., Verveer, L.: Learning from video modeling examples: effects of seeing the human model’s face. Comput. Educ. 72, 323–327 (2014)

    Article  Google Scholar 

  19. Worsley, M., Blikstein, P.: What’s an expert? Using learning analytics to identify emergent markers of expertise through automated speech, sentiment and sketch analysis. In: Educational Data Mining Conference, pp. 235–240 (2011)

    Google Scholar 

  20. Yang, D., Kraut, R., Rose, C.: Exploring the effect of student confusion in massive open online courses. J. Educ. Data Min. 8(1), 52–83 (2016)

    Google Scholar 

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Correspondence to Kasia Muldner .

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Stranc, S., Muldner, K. (2019). Learning from Videos Showing a Dialog Fosters More Positive Affect Than Learning from a Monolog. In: Isotani, S., Millán, E., Ogan, A., Hastings, P., McLaren, B., Luckin, R. (eds) Artificial Intelligence in Education. AIED 2019. Lecture Notes in Computer Science(), vol 11626. Springer, Cham. https://doi.org/10.1007/978-3-030-23207-8_51

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  • DOI: https://doi.org/10.1007/978-3-030-23207-8_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-23206-1

  • Online ISBN: 978-3-030-23207-8

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