MOOCs, Automation, Artificial Intelligence and Pedagogical Agents
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MOOCs, Automation, Artificial Intelligence and Pedagogical Agents

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Open courses are a sociocultural phenomenon. This phenomenon represents symptoms, responses, and failures facing Higher Education. In this talk, I examined open courses and MOOCs from a variety of ...

Open courses are a sociocultural phenomenon. This phenomenon represents symptoms, responses, and failures facing Higher Education. In this talk, I examined open courses and MOOCs from a variety of angles and discussed the degree to which MOOCs have portrayed education as a product that can be packaged, automated, and delivered. Empirical research on the design and development of pedagogical and intelligent agents that may be used in MOOCs was also presented. More information here: http://www.veletsianos.com/2014/06/05/moocs-automation-artificial-intelligence-seminar/

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MOOCs, Automation, Artificial Intelligence and Pedagogical Agents MOOCs, Automation, Artificial Intelligence and Pedagogical Agents Presentation Transcript

  • MOOCs, Automation, Artificial Intelligence and Pedagogical Agents George Veletsianos, PhD Canada Research Chair, Associate Professor School of Education and Technology, Royal Roads University June 18, 2014 :: University of Edinburgh
  • School of Education and Technology http://tinyurl.com/RRUMALAT
  • An opportune time
  • Today’s roadmap 1.  The MOOC as a sociocultural phenomenon 2.  Automation of teaching historically, and in the context of MOOCs 3.  Pedagogical agents as teaching automation artifacts in online learning
  • - #change11 cMOOC - MOOCs repurposed in my courses (for student analyses) - Teaching an open course in the Fall (Networked Scholars - #scholar14) - Research agenda focuses on experiences in emerging online settings (e.g., open courses, social media, pedagogical agents)
  • - #change11 cMOOC - MOOCs repurposed in my courses (for student analyses) - Teaching an open course in the Fall (Networked Scholars - #scholar14) - Research agenda focuses on experiences in emerging online settings (e.g., open courses, social media, pedagogical agents)
  • The MOOC as a sociocultural phenomenon (with Rolin Moe)
  • If the MOOC is not just a learning model, what is it? •  A response to increasing costs
  • If the MOOC is not just a learning model, what is it? •  A response to increasing costs •  A symptom of the belief that education à workforce training
  • If the MOOC is not just a learning model, what is it? •  A response to increasing costs •  A symptom of the belief that education à workforce training •  Representative of current political landscape
  • If the MOOC is not just a learning model, what is it? •  A response to increasing costs •  A symptom of the belief that education à workforce training •  Representative of the current political landscape •  Representative of the perspective that technology provides solutions
  • If the MOOC is not just a learning model, what is it? •  A response to increasing costs •  A symptom of the belief that education à workforce training •  Representative of the current political landscape •  Representative of the perspective that technology provides solutions •  Indicative of scholarly failures
  • If the MOOC is not just a learning model, what is it? •  A response to increasing costs •  A symptom of the belief that education à workforce training •  Representative of the current political landscape •  Representative of the perspective that technology provides solutions •  Indicative of scholarly failures •  Representative of the belief that education can be packaged and automated
  • The automation of teaching
  • An “industrial revolution” must occur in education, one “in which educational science and the ingenuity of educational technology combine to modernize the grossly inefficient and clumsy procedures of conventional education.” Pressey (1933, pp. 582)
  • His solution: Teaching Machines, devices that he was contemplating as early as 1915 (Benjamin, 1988).
  • B.F. Skinner’s 1935 Teaching Machine
  • Basulto (2014) predicts an “artificially intelligent machine” could teach massive open online courses, “lecturing, grading and engaging with students…Unlike humans, machines would be willing to complete all the coursework and do all the assignments…”
  • “With the menial job of checking and grading assignments taken over by computers, we (human teachers) will be left with the responsibility to intervene and mentor our students” (Yair, 2014 in ACM Inroads) The Automatic Teacher would free the teacher “from mechanical tasks… so that she may be a real teacher, not largely a clerical worker” (Pressey, 1927)
  • Enamored with effectiveness and efficiency
  • Margie’s future schoolroom in 2157 was “right next to the bedroom, and the mechanical teacher was on and waiting for her… [all the] lessons were shown and the questions were asked [on the big screen].” Asimov (1951)
  • “Regressive trend” toward mass production, commercialization, and commodification. Noble (1988)
  • Has the trend materialized? “strong pressures to produce mediocre instructional products based on templates and preexisting content” (Wilson, Parrish, & Veletsianos, 2008, pp.42) “Shovelware” = information masquerading as a course. (Morrison & Anglin, 2006)
  • Let’s unpack “automation.” Is automation the norm in academia already?
  • Social media automation Cross-posting (e.g., Facebook – Twitter) Pingbacks (blog comments) Blog post alerts (e.g., Facebook, Twitter, Linkedin)
  • Digital literacies? Scholarly literacies? We should contrast these activities to the automation of teaching that is evident in some MOOC practices & in some MOOCs.
  • Case Study
  • Tools à Functions Email Scheduler à coordination Study Group via OpenStudy à Pedagogical Support Interactive coding via Codeacademy à Assessment Ponti (in press)
  • These artifacts “remove the need for exposure to teachers, by providing participants with peer interactions and automated coordination and testing” (Ponti, in press)
  • Automated courses: for learners that are independent, self-organized, intrinsically motivated and capable? (Ponti in press; Tomkin & Charlevoix, 2014)
  • However, even though “MOOC teaching functions are often disaggregated and delegated to automated processes and community-based social learning, the place and visibility of the teacher remain of central importance.” (Bayne & Ross, 2014)
  • Learners describe “a unique and powerful sphere of intimacy that developed for them with their xMOOC instructor, most especially in the context of the pre-recorded instructional videos” Adams, C., Yin, Y., Vargas Madriz, L. F., & Mullen, C. S. (in press). A phenomenology of learning large: the tutorial sphere of xMOOC video lectures. Distance Education.
  • The case of “Mary,” who wrote a short story instead of an essay and shared the story on a MOOC discussion board
  • “The professor was totally checked out, he never visited the discussion board… and it was just depressing and discouraging And I thought his videos were not valuable at all so I didn’t watch them. So, it was almost like that course didn’t have an instructor …there was someone who built the class and created the reading but that was it.”
  • The artifacts in the Mechanical MOOC reconfigured facilitation/instruction. What other functions can automated artifacts play?
  • Pedagogical agents
  • What or Who is a pedagogical agent? “A virtual character employed in a digital learning environments to serve various educational goals.”
  • … and not just pedagogical
  • Back to education: What kinds of goals? Learning Motivation Engagement Encouragement Comfort Believability Play & Fun
  • Complexity of the field •  Empirical evidence in support of the prior claims (motivation, comfort, etc) is mixed, and often ambiguous.
  • If you were to design a pedagogical agent, what choices would you make, and what would those choices depend on?
  • Example #1: Gender Gulz et al; Kim & colleagues; Baylor & colleagues
  • Contextual relevance Veletsianos 2007, 2010
  • Example #2: Agent appearance Domagk (2010) - Including an agent = no impact on learning (expected) - Appealing agents promoted transfer - Unappealing agents hindered learning
  • Agent-learner relationships & agent-learner interactions •  A few studies in educational contexts - not the majority •  These studies occur in open-ended environments (not the norm in the field) •  Emerging evidence: enjoyment of social chat, verbal abuse, fun with the system •  Computers As Social Actors (Media equation), Uncanny valley
  • Research Questions •  What topics are discussed in agent-learner conversations? •  What social practices emerge in agent- learner conversations?
  • Series of studies •  Students have access to agents for weeks at a time •  Naturalistic settings •  Variety of methods: Computer Mediated Discourse Analysis, phenomenology, open coding using standard interpretive lens, quasi-experimental
  • Results #1: Small-talk •  Hey Mark, how are you today? •  Did you watch the [football] game last night?
  • Results #2: Playfulness •  Did you watch the [football] game last night? •  Do you have a girl/boyfriend?
  • Results #3: Abusive/aggressive comments •  You stupid [expletive]! •  shut up. Don’t correct me. •  Agent: I can’t answer that. User: WHY NOT!? “The fact that he couldn't help me made me really angry… I don’t remember what the question was but [the agent] should
  • Conflicts “I hated Joan or whatever the super- agent lady was called. She asked me at one point 'Are you testing me?' like we were going to have some sort of a confrontation or something. I've never wanted to hurt a digital person before!”
  • Results #4: Sharing personal information •  I am worried about my exam score •  My girlfriend broke up with me
  • Results #5: Agent Role •  Agent as instructor/learning companion (results from prior literature) •  Agent as mediator –  Can you tell professor X that she needs to program you better? •  Agent as partner (sometimes you just want to talk) –  This was an easy assignment, Mark.
  • •  Social and psychological issues are as significant as technology design issues. •  How would results differ: –  with different agents? (e.g., appearance) – with agents of varied social intelligence? – in MOOCs – in studies of shorter/longer duration?
  • Perhaps what we need is a Turing test for MOOC instruction
  • Is your MOOC instructor a person or a bot?
  • Thank you! www.veletsianos.com www.veletsianos.com/publications @veletsianos on Twitter veletsianos at gmail.com