311
Views
0
CrossRef citations to date
0
Altmetric
Research Articles

Examining perceptions and outcomes of AI versus human course assistant discussions in the online classroom

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon

References

  • Abendschein, B., Edwards, C., Edwards, A., Rijhwani, V., & Stahl, J. (2021). Human–robot learning configurations: A study of interpersonal communication perceptions and affective learning in higher education. Journal of Communication Pedagogy, 4, 123–132. https://doi.org/10.31446/JCP.2021.1.12
  • Baringer, D. K., & McCroskey, J. C. (2000). Immediacy in the classroom: Student immediacy. Communication Education, 49(2), 178–186. https://doi.org/10.1080/03634520009379204
  • Blackboard. (2023). Blackboard learn AI design assistant. https://help.blackboard.com/Learn/Administrator/SaaS/Tools_Management/Learn_AI_Design_Assistant
  • Bodkin, H. (2017, September 11). ‘Inspirational’ robots to begin replacing teachers within 10 years. The Telegraph. https://web.archive.org/web/20170911022020/https://www.telegraph.co.uk/science/2017/09/11/inspirational-robots-begin-replacing-teachers-within-10-years/
  • Bouchrika, I. (2023). 51 LMS statistics: 2023 data, trends & predictions. Research.com https://web.archive.org/web/20230723113646/https://research.com/education/lms-statistics
  • Bowman, N. D., & Keene, J. R. (2018). A layered approach for considering open science practices. Communication Research Reports, 35(4), 363–372. https://doi.org/10.1080/08824096.2018.1513273
  • Bowman, N. D., & Spence, P. R. (2020). Challenges and best practices associated with sharing research materials and research data for communication scholars. Communication Studies, 71(4), 708–716. https://doi.org/10.1080/10510974.2020.1799488
  • Bowman, N. D., Spence, P. R., & Hahn, L. (2023). Open, organized, and onerous: Understanding and recognizing the labors of open science. Journal of the Association for Communication Administration, 40, 61–70.
  • Chai, C. S., Lin, P. Y., Jong, M. S. Y., Dai, Y., Chiu, T. K., & Qin, J. (2021). Perceptions of and behavioral intentions towards learning artificial intelligence in primary school students. Educational Technology & Society, 24(3), 89–101. https://www.jstor.org/stable/27032858
  • Chen, M., Liu, F., & Lee, Y. H. (2022, May). My tutor is an AI: The effects of involvement and tutor type on perceived quality, perceived credibility, and Use intention. In International conference on human-computer interaction (pp. 232–244). Springer International Publishing. https://doi.org/10.1007/978-3-031-05643-7_15.
  • Chiu, T. K. (2021). A holistic approach to the design of artificial intelligence (AI) education for K-12 schools. TechTrends, 65(5), 796–807. https://doi.org/10.1007/s11528-021-00637-1
  • Clark-Gordon, C. V., & Goodboy, A. K. (2020). Instructor self-disclosure and third-party generated warrants: Student perceptions of professor social media use. Western Journal of Communication, 84(1), 79–97. https://doi.org/10.1080/10570314.2019.1649453
  • Edwards, C., Edwards, A., Spence, P. R., & Shelton, A. K. (2014). Is that a bot running the social media feed? Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twiter. Computers in Human Behavior, 33, 372–376. https://doi.org/10.1016/j.chb.2013.08.013
  • Edwards, A., Edwards, C., Spence, P. R., Harris, C., & Gambino, A. (2016). Robots in the classroom: Differences in students’ perceptions of credibility and learning between “teacher as robot” and “robot as teacher”. Computers in Human Behavior, 65, 627–634. https://doi.org/10.1016/j.chb.2016.06.005
  • Edwards, C., & Craig, M. J. A. (2023). HMC in the educational context. In A. Guzman, R. McEwen, & S. Jones (Eds.), The SAGE handbook of human-machine communication. (pp. 500–506). SAGE Publications Ltd. https://doi.org/10.4135/9781529782783
  • Edwards, C., Edwards, A., Albrehi, F., & Spence, P. (2021). Interpersonal impressions of a social robot versus human in the context of performance evaluations. Communication Education, 70(2), 165–182. https://doi.org/10.1080/03634523.2020.1802495
  • Edwards, C., Edwards, A., Spence, P. R., & Lin, X. (2018). I, teacher: Using artificial intelligence (AI) and social robots in communication and instruction. Communication Education, 67(4), 473–480. https://doi.org/10.1080/03634523.2018.1502459
  • Edwards, C., Edwards, A., Spence, P. R., & Westerman, D. (2016). Initial interaction expectations with robots: Testing the human-to-human interaction script. Communication Studies, 67(2), 227–238. https://doi.org/10.1080/10510974.2015.1121899
  • Edwards, C., Edwards, A., Stoll, B., Lin, X., & Massey, N. (2019). Evaluations of an artificial intelligence instructor's voice: Social identity theory in human–robot interactions. Computers in Human Behavior, 90, 357–362. https://doi.org/10.1016/j.chb.2018.08.027
  • Edwards, C., Stoll, B., Edwards, A., Spence, P. R., & Gambino, A. (2018). I’ll present to the human”: effects of a robot evaluator on anticipatory public speak anxiety. In A. Guzman (Ed.), Human-Machine communication: Rethinking communication, technology, and ourselves (pp. 83–97). Peter Lang.
  • Fernández-Llamas, C., Conde, M. A., Rodríguez-Lera, F. J., Rodríguez-Sedano, F. J., & García, F. (2018). May I teach you? Students’ behavior when lectured by robotic vs. Human teachers. Computers in Human Behavior, 80, 460–469. https://doi.org/10.1016/j.chb.2017.09.028
  • Gambino, A., Fox, J., & Ratan, R. A. (2020). Building a stronger CASA: Extending the computers Are social actors paradigm. Human-Machine Communication, 1, 71–86. https://doi.org/10.30658/hmc.1.5
  • Garg, A. (2023, June 28). ChatGPT now replacing teachers? Harvard University's CS teacher is an AI chatbot. India Today. https://web.archive.org/web/20230701064824/https://www.indiatoday.in/technology/news/story/chatgpt-now-replacing-teachers-harvard-university-computer-science-teacher-is- ai-chatbot-2399189-2023-06-28
  • Goodboy, A. K., & Bolkan, S. (2009). College teacher misbehaviors: Direct and indirect effects on student communication behavior and traditional learning outcomes. Western Journal of Communication, 73(2), 204–219. https://doi.org/10.1080/10570310902856089
  • Goodboy, A. K., Martin, M. M., & Bolkan, S. (2009). The development and validation of the student communication satisfaction scale. Communication Education, 58(3), 372–396. https://doi.org/10.1080/03634520902755441
  • Graham, E. E., Walter, H. L., & Tang, T. (2022). The influence of course format, student characteristics, and perceived teacher communication and behavior on instructional outcomes before and during the COVID-19 pandemic. Journal of Communication Pedagogy, 6, 231–254. https://doi.org/10.31446/JCP.2022.1.17
  • Gunawardena, C. N. (1995). Social presence theory and implications for interaction and collaborative learning in computer conferences. International Journal of Educational Telecommunications, 1, 147–166.
  • Ishii, K., Spence, P. R., & Hodges, W. R. (2021). Social presence in computer-based receptionists: Experimental study towards organizational automation. Communication Reports, 34(2), 92–105. https://doi.org/10.1080/08934215.2021.1918199
  • Jiang, Y., Ho, Y. C., Yan, X., & Tan, Y. (2022). What’s in a “username”? The effect of perceived anonymity on herding in crowdfunding. Information Systems Research, 33(1), 1–17. https://doi.org/10.1287/isre.2021.104
  • Karimi, S., & Wang, F. (2017). Online review helpfulness: Impact of reviewer profile image. Decision Support Systems, 96, 39–48. https://doi.org/10.1016/j.dss.2017.02.001
  • Kaufmann, R., Sellnow, D. D., & Frisby, B. N. (2016). The development and validation of the online learning climate scale (OLCS). Communication Education, 65(3), 307–321. https://doi.org/10.1080/03634523.2015.1101778
  • Kaufmann, R., & Vallade, J. I. (2021). Online student perceptions of their communication preparedness. E-learning and Digital Media, 18(1), 86–104. https://doi.org/10.1177/2042753020950873
  • Kaufmann, R., & Vallade, J. I. (2022). Exploring connections in the online learning environment: Student perceptions of rapport, climate, and loneliness. Interactive Learning Environments, 30(10), 1794–1808. https://doi.org/10.1080/10494820.2020.1749670
  • Kendall, K. D., & Schussler, E. E. (2012). Does instructor type matter? Undergraduate student perception of graduate teaching assistants and professors. CBE—Life Sciences Education, 11(2), 187–199. https://doi.org/10.1187/cbe.11-10-0091
  • Kim, J., Merrill, K., Xu, K., & Kelly, S. (2022). Perceived credibility of an AI instructor in online education: The role of social presence and voice features. Computers in Human Behavior, 136, 107383. https://doi.org/10.1016/j.chb.2022.107383
  • Kim, J., Merrill, K., Xu, K., & Sellnow, D. D. (2020). My teacher is a machine: Understanding students’ perceptions of AI teaching assistants in online education. International Journal of Human–Computer Interaction, 36(20), 1902–1911. https://doi.org/10.1080/10447318.2020.1801227
  • Kim, J., Merrill, K., Xu, K., & Sellnow, D. D. (2022). Embracing AI-based education: Perceived social presence of human teachers and expectations about machine teachers in online education. Human-Machine Communication, 4, 169–185. https://doi.org/10.30658/hmc.4.9
  • Kucuk, S., & Sisman, B. (2020). Students’ attitudes towards robotics and STEM: Differences based on gender and robotics experience. International Journal of Child-Computer Interaction, 23-24, 100167. https://doi.org/10.1016/j.ijcci.2020.100167
  • Lee, Y. E., Simon, L. S., Koopman, J., Rosen, C. C., Gabriel, A. S., & Yoon, S. (2023). When, why, and for whom is receiving help actually helpful? Differential effects of receiving empowering and nonempowering help based on recipient gender. Journal of Applied Psychology, 108(5), 773–793. https://doi.org/10.1037/apl0001049
  • Lin, X., Kaufmann, R., Spates, S. A., Lachlan, K. A., & Spence, P. R. (2022). Exploring students' perceptions of identity and helper heuristics in the online classroom discussion board. Communication Education, 71(2), 108–124. https://doi.org/10.1080/03634523.2021.1957138
  • Lin, X., Kaufmann, R., Spence, P. R., & Lachlan, K. A. (2019). Agency cues in online comments: Exploring their relationship with anonymity and frequency of helpful posts. Southern Communication Journal, 84(3), 183–195. https://doi.org/10.1080/1041794X.2019.1584828
  • Lin, X., & Spence, P. R. (2018). Identity on social networks as a cue: Identity, retweets, and credibility. Communication Studies, 69(5), 461–482. https://doi.org/10.1080/10510974.2018.1489295
  • Lin, X., & Spence, P. R. (2019). Others share this message, so we can trust it? An examination of bandwagon cues on organizational trust in risk messages. Information Processing & Management, 56(4), 1559–1564. https://doi.org/10.1016/j.ipm.2018.10.006
  • Lin, X., Spence, P. R., & Lachlan, K. A. (2016). Social media and credibility indicators: The effect of influence cues. Computers in Human Behavior, 63, 264–271. https://doi.org/10.1016/j.chb.2016.05.002
  • Lombard, M., & Xu, K. (2021). Social responses to media technologies in the 21st century: The media are social actors paradigm. Human-Machine Communication, 2, 29–55. https://doi.org/10.30658/hmc.2.2
  • Macsinga, I., Sulea, C., Sârbescu, P., Fischmann, G., & Dumitru, C. (2015). Engaged, committed and helpful employees: The role of psychological empowerment. The Journal of Psychology, 149(3), 263–276. https://doi.org/10.1080/00223980.2013.874323
  • Martin, F., Wang, C., & Sadaf, A. (2018). Student perception of helpfulness of facilitation strategies that enhance instructor presence, connectedness, engagement and learning in online courses. The Internet and Higher Education, 37, 52–65. https://doi.org/10.1016/j.iheduc.2018.01.003
  • McCroskey, J. C. (1994). Assessment of affect toward communication and affect toward instruction in communication. In S. Morreale, & M. Brooks (Eds.), 1994 SCA summer conference proceedings and prepared remarks: Assessing college student competence in speech communication. Speech Communication Association.
  • McCroskey, J. C., & McCain, T. A. (1974). The measurement of interpersonal attraction. Speech Monographs, 41(3), 261–266. https://doi.org/10.1080/03637757409375845
  • McCroskey, J. C., & Teven, J. J. (1999). Goodwill: A reexamination of the construct and its measurement. Communication Monographs, 66(1), 90–103. https://doi.org/10.1080/03637759909376464
  • Metzger, M. J., Flanagin, A. J., Eyal, K., Lemus, D. R., & McCann, R. M. (2003). Credibility for the 21st century: Integrating perspectives on source, message, and media credibility in the contemporary media environment. Annals of the International Communication Association, 27(1), 293–335. https://doi.org/10.1080/23808985.2003.11679029
  • Meyer, P. (1988). Defining and measuring credibility of newspapers: Developing an index. Journalism Quarterly, 65(3), 567–574. https://doi.org/10.1177/107769908806500301
  • Mishra, P. (2006). Affective feedback from computers and its effect on perceived ability and affect: A test of the computers as social actor hypothesis. Journal of Educational Multimedia and Hypermedia, 15(1), 107–131.
  • Myers, S. A., Goodboy, A. K., & Members of Comm 600 (2014). College student learning, motivation, and satisfaction as a function of effective instructor communication behaviors. Southern Communication Journal, 79(1), 14–26. https://doi.org/10.1080/1041794X.2013.815266
  • O’Keefe, D. J. (2002). Persuasion: Theory & research (2nd ed). Sage.
  • Reeves, B., & Nass, C. (1996). The media equation: How people treat computers, television, and new media like real people and places. Center for the Study of Language and Information.
  • Richards, R. J., Spence, P. R., & Edwards, C. C. (2022). Human-machine communication scholarship trends: An examination of research from 2011 to 2021 in communication journals. Human-Machine Communication, 4, 45–65. https://doi.org/10.30658/hmc.4.3
  • Schroeder, N. L., Chiou, E. K., & Craig, S. D. (2021). Trust influences perceptions of virtual humans, but not necessarily learning. Computers & Education, 160, 104039. https://doi.org/10.1016/j.compedu.2020.104039
  • Sidelinger, R. J., & Bolen, D. M. (2016). Instructor credibility as a mediator of instructors’ compulsive communication and student communication satisfaction in the college classroom. Communication Research Reports, 33(1), 24–31. https://doi.org/10.1080/08824096.2015.1117438
  • Sidelinger, R. J., Nyeste, M. C., Madlock, P. E., Pollak, J., & Wilkinson, J. (2015). Instructor privacy management in the classroom: Exploring instructors’ ineffective communication and student communication satisfaction. Communication Studies, 66(5), 569–589. https://doi.org/10.1080/10510974.2015.1034875
  • Spates, S. A., Kaufmann, R., Lin, X., Lachlan, K. A., & Spence, P. R. (2020). I don’t care about who you are, but what you are for me? Examining perceptions of helpful comments and identity in user-generated content. Southern Communication Journal, 85(3), 155–165. https://doi.org/10.1080/1041794X.2020.1770319
  • Spence, P. R. (2019). Searching for questions, original thoughts, or advancing theory: Human- machine communication. Computers in Human Behavior, 90, 285–287. https://doi.org/10.1016/j.chb.2018.09.014
  • Spence, P. R., Edwards, A., Edwards, C., & Jin, X. (2019). The bot predicted rain, grab an uumbrella’: Few perceived differences in communication quality of a weather twitterbot versus professional and amateur meteorologists. Behaviour & Information Technology, 38(1), 101–109. https://doi.org/10.1080/0144929X.2018.1514425
  • Spence, P. R., Edwards, C., Edwards, A., Rainear, A., & Jin, X. (2021). They’re always wrong anyway”: exploring differences of credibility, attraction, and behavioral intentions in professional, amateur, and robotic-delivered weather forecasts. Communication Quarterly, 69(1), 67–86. https://doi.org/10.1080/01463373.2021.1877164
  • Spence, P. R., Kauffman, R., Lachlan, K. A., Lin, X., & Spates, S. A. (2023). Extending the understanding of online discussions: A replication of online students’ perceptions of identity and helper heuristics. Communication Education, 72(4), 367–381. https://doi.org/10.1080/03634523.2023.2169315
  • Spence, P. R., Lachlan, K. A., Edwards, A., & Edwards, C. (2016). Tweeting fast matters, but only if I think about it: Information updates on social media. Communication Quarterly, 64(1), 55–71. https://doi.org/10.1080/01463373.2015.1100644
  • Spence, P. R., Westerman, D., & Luo, Z. (2023). Observing communication with machines. In A. Guzman, R. McEwen, & S. Jones (Eds.), The sage handbook of human machine communication (pp. 220–227). Sage Publications. https://doi.org/10.4135/9781529782783.n27.
  • Spitzberg, B. H. (2006). Preliminary development of a model and measure of computer-mediated communication (CMC) competence. Journal of Computer-Mediated Communication, 11(2), 629–666. https://doi.org/10.1111/j.1083-6101.2006.00030.x
  • Sundar, S. S. (2008). The MAIN model: A heuristic approach to understanding technology effects on credibility. In M. J. Metzger, & A. J. Flanagin (Eds.), Digital media, youth, and credibility: The John D. And Catherine T. MacArthur foundation series on digital media and learning (pp. 73–100). The MIT Press. https://doi.org/10.1162/dmal.9780262562324.073.
  • Tandoc Jr, E. C., Yao, L. J., & Wu, S. (2020). Man vs. Machine? The impact of algorithm authorship on news credibility. Digital Journalism, 8(4), 548–562. https://doi.org/10.1080/21670811.2020.1762102
  • van der Goot, M. J., & Etzrodt, K. (2023). Disentangling two fundamental paradigms in human-machine communication research: Media equation and media evocation. Human-Machine Communication, 6, 17–30. https://doi.org/10.30658/hmc.6.2
  • Vasagar, J. (2017, July 12). How robots are teaching Singapore’s kids. The Financial Times. https://web.archive.org/web/20201001195329/https://www.ft.com/content/f3cbfada-668e- 11e7-8526-7b38dcaef614
  • Vazire, S., & Gosling, S. D. (2004). E-Perceptions: Personality impressions based on personal websites. Journal of Personality and Social Psychology, 87(1), 123–132. https://doi.org/10.1037/0022-3514.87.1.123
  • Walther, J. B. (2007). Selective self-presentation in computer-mediated communication: Hyperpersonal dimensions of technology, language, and cognition. Computers in Human Behavior, 23(5), 2538–2557. https://doi.org/10.1016/j.chb.2006.05.002
  • Westerman, D., Cross, A. C., & Lindmark, P. G. (2019). I believe in a thing called bot: Perceptions of the humanness of “chatbots”. Communication Studies, 70(3), 295–312. https://doi.org/10.1080/10510974.2018.1557233
  • Westerman, D., Spence, P. R., & Van Der Heide, B. (2014). Social media as information source: Recency of updates and credibility of information. Journal of Computer-Mediated Communication, 19(2), 171–183. https://doi.org/10.1111/jcc4.12041
  • Westerman, D. W., Spence, P. R., & Van Der Heide, B. (2012). A social network as information: The effect of system generated reports of connectedness on credibility and health care information on twitter. Computers in Human Behavior, 28(1), 199–206. https://doi.org/10.1016/j.chb.2011.09.001
  • Williams, J. (2023, August 17). Instructure. https://community.canvaslms.com/t5/Artificial-Intelligence-in/Use-AI-to-Author-Better-Outcomes-Right-in-Canvas/ba-p/576772
  • Williams, R., Park, H. W., Oh, L., & Breazeal, C. (2019, July). Popbots: Designing an artificial intelligence curriculum for early childhood education. In Proceedings of the AAAI Conference on Artificial Intelligence, 33(1), 9729–9736. https://doi.org/10.1609/aaai.v33i01.33019729
  • Wood, A. M., Froh, J. J., & Geraghty, A. W. (2010). Gratitude and well-being: A review and theoretical integration. Clinical Psychology Review, 30(7), 890–905. https://doi.org/10.1016/j.cpr.2010.03.005
  • Yang, S., Zhou, Y., Yao, J., Chen, Y., & Wei, J. (2019). Understanding online review helpfulness in omnichannel retailing. Industrial Management & Data Systems, 119(8), 1565–1580. https://doi.org/10.1108/IMDS-10-2018-0450
  • Zapf, D. (2002). Emotion work and psychological well-being: A review of the literature and some conceptual considerations. Human Resource Management Review, 12(2), 237–268. https://doi.org/10.1016/S1053-4822(02)00048-7
  • Zhu, L., Yin, G., & He, W. (2014). Is this opinion leader’s review useful? Peripheral cues for online review helpfulness. Journal of Electronic Commerce Research, 15(4), 267–280.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.