Skip to main content

Advertisement

Log in

Humanizing Instructional Videos in Physics: When Less Is More

  • Published:
Journal of Science Education and Technology Aims and scope Submit manuscript

Abstract

Many instructors in science, technology, engineering, and mathematics fields are striving to create active learning environments in their classrooms and in doing so are frequently moving the lecture portion of their course into online video format. In this classroom-based study, we used a two group randomized experimental design to examine the efficacy of an instructional video that incorporates a human hand demonstrating and modeling how to solve frictional inclined plane problems compared to an identical video that did not include the human hand. The results show that the learners who viewed the video without the human hand present performed significantly better on a learning test and experienced a significantly better training efficiency than the learners who viewed the video with the human hand present. Meanwhile, those who learned with the human hand present in the instructional video rated the instructor as being more humanlike and engaging. The results have implications for both theory and practice. Implications for those designing instructional videos are discussed, as well as the limitations of the current study.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Arons AB (1996) Teaching introductory physics, 1 edn. Wiley, New York

    Google Scholar 

  • Atkinson RK (2002) Optimizing learning from examples using animated pedagogical agents. J Educ Psychol 94(2):416–427

    Article  Google Scholar 

  • Baylor, A. L. (2011) The design of motivational agents and avatars. Educational Technology Research and Development, 59(2):291–300

  • Baylor AL, & Kim Y (2004) Pedagogical agent design: the impact of agent realism, gender, ethnicity, and instructional role. In Intelligent tutoring systems (pp. 592–603). Springer Berlin Heidelberg

  • Beichner B (2009) An Introduction to Physics Education Research. In C. Henderson & K. Harper (Eds.), Getting Started in PER (Vol. 2). American Association of Physics Teachers. Retrieved from http://www.per-central.org/items/detail.cfm?ID=8806

  • Bishop JL, & Verleger MA (2013) The flipped classroom: a survey of the research. In ASEE National Conference Proceedings (Vol. 30). Atlanta, GA

  • Chi MTH, Feltovich PJ, Glaser R (1981) Categorization and representation of physics problems by experts and novices. Cogn Sci 5(2):121–152

    Article  Google Scholar 

  • Clark RE, Choi S (2005) Five design principles for experiments on the effects of animated pedagogical agents. J Educ Comput Res 32(3):209–225

    Article  Google Scholar 

  • Clark RE, Choi S (2007) The questionable benefits of pedagogical agents: response to Veletsianos. J Educ Comput Res 36(4):379–381

    Article  Google Scholar 

  • Craig SD, Twyford J, Irigoyen N, Zipp SA (2015) A test of spatial contiguity for virtual human’s gestures in multimedia learning environments. J Educ Comput Res 53(1):3–14

    Article  Google Scholar 

  • Crampton, A., Vanniasinkam, T., & Ragusa, A. T. (2012). Microbial vodcasting—supplementing laboratory time with vodcasts of key microbial skills. In Proceedings of The Australian Conference on Science and Mathematics Education, 171–176.

  • Domagk S (2010) Do pedagogical agents facilitate learner motivation and learning outcomes? The role of the appeal of agent’s appearance and voice. J Media Psychol 22:84–97

    Article  Google Scholar 

  • Dunsworth Q, Atkinson RK (2007) Fostering multimedia learning of science: exploring the role of an animated agent’s image. Comput Educ 49:677–690

    Article  Google Scholar 

  • Field A (2013) Discovering statistics using IBM SPSS statistics. Sage Publications, Thousand Oaks

    Google Scholar 

  • Fiorella L, Mayer RE (2015) Effects of observing the instructor draw diagrams on learning from multimedia messages. J Educ Psychol. doi:10.1037/edu0000065

    Google Scholar 

  • Frechette C, Moreno R (2010) The roles of animated pedagogical agents’ presence and nonverbal communication in multimedia learning environments. J Media Psychol 22(2):61–72

    Article  Google Scholar 

  • Freeman S, Eddy SL, McDonough M, Smith MK, Okoroafor N, Jordt H, Wenderoth MP (2014) Active learning increases student performance in science, engineering and mathematics. Proc Natl Acad Sci 111(23):8410–8415

    Article  Google Scholar 

  • Ginns P (2005) Meta-analysis of the modality effect. Learn Instr 15(4):313–331

    Article  Google Scholar 

  • Hake, R. R. (1998) Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. Am J Phys 66(1):64–74

  • Hammer, D. (1996) More than misconceptions: Multiple perspectives on student knowledge and reasoning, and an appropriate role for education research. Am J Phys 64(10):1316–1325

  • Halloun IA, Hestenes D (1985) Common sense concepts about motion. Am J Phys 53(11):1056–1065

    Article  Google Scholar 

  • Heidig S, Clarebout G (2011) Do pedagogical agents make a difference to student motivation and learning? Educ Res Rev 6:27–54

    Article  Google Scholar 

  • Hestenes D, Wells M, Swackhamer G (1992) Force concept inventory. Phys Teach 30(3):141–158

    Article  Google Scholar 

  • Huffman D, Heller P (1995) What does the force concept inventory actually measure? Phys Teach 33:138

    Article  Google Scholar 

  • Louwerse MM, Graesser AC, McNamara DS, Lu S (2009) Embodied conversational agents as conversational partners. Appl Cogn Psychol 23:1244–2009

    Article  Google Scholar 

  • Martin BE, Connors M (2003) Testing a model for sliding motion on an incline. Phys Teach 41(9):534–536

    Article  Google Scholar 

  • Mattis KV (2015) Flipped classroom versus traditional textbook instruction: assessing accuracy and mental effort at different levels of mathematical complexity. Technol Knowl Learn 20:231–248

    Article  Google Scholar 

  • Mayer RE (Ed.). (2014a) The Cambridge handbook of multimedia learning (2nd edition). New York, NY: The Cambridge University Press.

  • Mayer RE (2014b) Principles based on social cues in multimedia learning: personalization, voice, image, and embodiment principles. In R. Mayer (Ed.), The Cambridge handbook of multimedia learning (2nd edition) (pp. 345–368).

  • Mayer RE, Sobko K, Mautone PD (2003) Social cues in multimedia learning: role of speaker’s voice. J Educ Psychol 95(2):419–425

    Article  Google Scholar 

  • McDermott LC, Redish EF (1999) Resource letter: PER-1: physics education research. Am J Phys 67(9):755–767

    Article  Google Scholar 

  • Moreno R (2005) Multimedia learning with animated pedagogical agents. In R. E. Mayer’s (Ed.), The Cambridge handbook of multimedia learning (pp. 507–523). New York, NY: Cambridge University Press.

  • Moreno R, Flowerday T (2006) Students’ choice of animated pedagogical agents in science learning: a test of the similarity-attraction hypothesis on gender and ethnicity. Contemp Educ Psychol 31(2):186–207

    Article  Google Scholar 

  • Moreno R, Mayer RE, Spires HA, Lester JC (2001) The case for social agency in computer-based teaching: do students learn more deeply when they interact with animated pedagogical agents? Cogn Instr 19(2):177–213

    Article  Google Scholar 

  • National Research Council (2000) How people learn: brain, mind, experience, and school, Expanded edn. The National Academies Press, Washington, D.C. Retrieved from http://www.nap.edu/catalog/9853/how-people-learn-brain-mind-experience-and-school-expanded-edition

    Google Scholar 

  • National Research Council (2013) Adapting to a changing world—challenges and opportunities in undergraduate physics education. The National Academies Press, Washington, D.C. Retrieved from http://www.nap.edu/catalog.php?record_id=18312

    Google Scholar 

  • Ozogul G, Johnson AM, Atkinson RK, Reisslein M (2013) Investigating the impact of pedagogical agent gender matching and learner choice on learning outcomes and perceptions. Comput Educ 67:36–50

    Article  Google Scholar 

  • Paas F (1992) Training strategies for attaining transfer of problem-solving skill in statistics: a cognitive-load approach. J Educ Psychol 84:429–434

    Article  Google Scholar 

  • Paas F, & Sweller J (2014) Implications of cognitive load theory for multimedia learning. In. R. E. Mayer’s The Cambridge handbook of multimedia learning (2nd ed.)(pp. 27–42.). New York, NY: Cambridge University Press

  • Paas F, Tuovinen JE, Tabbers H, Van Gerven PWM (2003) Cognitive load measurement as a means to advance cognitive load theory. Educ Psychol 38(1):63–71

    Article  Google Scholar 

  • Paas F, van Merriënboer JJG (1993) The efficiency of instructional conditions: an approach to combine mental effort and performance measures. Hum Factors 35(4):737–743

    Google Scholar 

  • Reeves B, Nass C (1996) The media equation: how people treat computers, television, and new media like real people and places. CSLI Publications, Stanford

    Google Scholar 

  • Rosengrant D, Van Heuvelen A, Etkina E (2009) Do students use and understand free-body diagrams? Phys Rev Special Topics - Phys Educ Res 5(1):010108

    Article  Google Scholar 

  • Ryu J, Baylor AL (2005) The psychometric structure of pedagogical agent persona. Technol Instr Cogn Learn 2:291–314

    Google Scholar 

  • Schroeder, N. L., Adesope, O. O., & Gilbert, R. B (2013) How effective are pedagogical agents for learning? A meta-analytic review. J. Educ. Comput. Res. 49(1):1–39

  • Schroeder, N. L. & Adesope, O. O. (2013) How does a contextually-relevant peer pedagogical agent in a learner-attenuated system-paced learning environment affect learner’s cognitive and affective outcomes? Journal of Teaching and Learning with Technology, 2(2):114–133

  • Schroeder, N. L., & Gotch, C. M. (2015) Persisting issues in pedagogical agent research. J. Educ. Comput. Res. 53(2):183–204

  • Schroeder, N. L., & Adesope, O. O. (2015) Impacts of pedagogical agent gender in an accessible learning environment. Educ. Technol. Soc. 18(4):401–411

  • Schroeder, N. L. (2016) A preliminary investigation of the influences of refutation text and instructional design. Technology, Knowledge, and Learning, 21:325–340

  • Sweller, J. (2005). Implications of cognitive load theory for multimedia learning. In R. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp.19–30). New York, NY: Cambridge University Press.

  • Sweller J (2010) Element interactivity and intrinsic, extraneous, and germane cognitive load. Educ Psychol Rev 22:123–138

    Article  Google Scholar 

  • Thornton RK, Sokoloff DR (1998) Assessing student learning of Newton’s laws: the force and motion conceptual evaluation and the evaluation of active learning laboratory and lecture curricula. Am J Phys 66(4):338–352

    Article  Google Scholar 

  • Van der Meij H (2013) Motivating agents in software tutorials. Comput Hum Behav 29(3):845–857

    Article  Google Scholar 

  • Veletsianos G (2010) Contextually relevant pedagogical agents: visual appearance, stereotypes, and first impressions and their impact on learning. Comput Educ 55(2):576–585

    Article  Google Scholar 

  • Wouters P, Paas F, van Merriënboer JJG (2008) How to optimize learning from animated models: a review of guidelines based on cognitive load. Rev Educ Res 78(3):645–675

    Article  Google Scholar 

  • Zappe S, Leicht R, Messner J, Litzinger T, & Lee HW (2009) “Flipping” the classroom to explore active learning in a large undergraduate course. In Proceedings of the American Society for Engineering Education Conference and Exposition. Session 92.

Download references

Acknowledgements

The authors would like to thank Todd Pavlack for his technical assistance in creating the instructional videos used in this study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Noah L. Schroeder.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schroeder, N.L., Traxler, A.L. Humanizing Instructional Videos in Physics: When Less Is More. J Sci Educ Technol 26, 269–278 (2017). https://doi.org/10.1007/s10956-016-9677-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10956-016-9677-6

Keywords

Navigation