What would be the point of Education if computers replace teachers?

Turing’s work on developing early versions of computers led to the imitation game as a way of investigating whether computers can think? The imitation game (Turing test) involves a participant in one room, a human confederate (someone whose behavior is under the direction of the experimenter) in another room and a computer terminal containing a program that simulates intelligence also in another room. The task for the participant is to decide which is human. In 1951 Turing predicted that by 2000 the average person, naïve to the fact that an interaction partner was a computer program, would assume humanness 70% of the time. Undoubtedly these ideas inspired the foundation of Artificial Intelligence (AI). Its subsequent evolution is brilliantly summarized on the BBC’s iWonder website http://www.bbc.co.uk/timelines/zq376fr.  In July 2015 an article on research that uses an echoborg (a human who acts as the mouthpiece for an artificial intelligence system) for the Turing test was featured on the BBC Futures website http://www.bbc.com/future/story/20150717-the-people-possessed-by-computers and for one week in September 2015  AI was a featured topic on the BBC reflecting a contemporary fascination with sharing our personal and working spaces with intelligent agents

However, the penetration of AI into Education (AIED) was not covered. AI techniques mean that artificial agents could replace teachers. An Intelligent tutor (IT), based on adaptive AI systems, means that learning contexts can be personalized for a student. The system (IT) uses a teacher-pupil model to adjust the learning task to an appropriate level and a task model to provide appropriate feedback to the student. Pedagogically sound opportunities to learn can be extended in both reach and frequency. A teacherbot has been used to answer student questions on a massive open online course (a MOOC). Teaching presence on MOOCs is sparse so that students who enroll on a MOOC need not incur a financial cost. Therefore, researchers are investigating ways in which the teacher can be assisted, or replaced by, a bot. https://www.timeshighereducation.co.uk/news/ask-teacherbot-are-robots-the-answer/2020326.article. Other examples of AI contributions include the ECHOES project that targets atypical development issues by using virtual agents to engage with children on the autism spectrum in order to improve their communication skills. http://echoes2.org/?q=node/2.

Versions of the headline ‘Intelligent agents replace teachers’ are increasingly common. ‘What if’ this transpires? with teachers replaced by AI products (robots, bots, virtual agents). What questions does it raise for Education? For example, what would it mean for a socio-cultural pedagogy that AI products are linguistically challenged and on current appraisal likely to remain so? Furthermore, the interdependence of emotion and cognition when learning is increasingly recognised, with empathy a foundational element of successful interpersonal interaction.  There is evidence from Neuroscience that both language and empathy are uniquely human capacities with dedicated brain structures and neural pathways. For a socio-cultural perspective meanings arise through social interaction and enable us to pursue personal goals and to think beyond the actual. It is social interaction that enables creativity. Therefore, it is significant that a recent report from Nesta concluded that ‘creative occupations are more future-proof to technologies like machine learning and mobile robotics’ http://www.nesta.org.uk/publications/creativity-vs-robots.

That the ability to transform knowledge and create history through social interaction is a uniquely human ability can be supported by evidence from Neuroscience. However, according to Kevin Warwick http://www.kevinwarwick.com, by comparison with computers, our human ability to communicate information is slow, limited in reach, and error prone and our reliance on language may become ‘excess baggage’. Educational Neuroscience, a multidisciplinary area that assesses the potential of Neuroscience for informing Education, could usefully contribute to the debate.

Teacherbot, useful tool or just another example of the allure of innovation

When I read the following article

Teacherbot: interventions in automated teaching by Sian Bayne. Teaching in Higher Education. Published online 16 Apr 2015. http://www.tandfonline.com/doi/10.1080/13562517.2015.1020783

I noted with interest that students had dropped the descriptor ‘teacher’ from the bot developed for the E-learning and digital cultures MOOC (University of Edinburgh).  Perhaps like me students could not discern any teacherly function of botty (the name that students adopted for teacherbot) that could not be otherwise achieved by providing a repository of curated resources and a frequently answered questions (FAQ) list.

Undoubtedly the agent that follows the MOOC hashtag (#edcmooc) and harvests student questions and comments is useful, but what did botty achieve? The behaviour of teacherbot (a rule based agent developed by the teachers to automate tweet responses) is problematic for me. Instead of making queries about the course (for example, about assessment procedure) available to all students in their collated form i.e. as a list of FAQs, botty responds to each student individually through twitter. Furthermore, although 60% of the enrolled students are postgraduates (as is the case for many MOOCs) with a professional interest in digital education botty pushes individual resources to individual students. Surely, for this demographic it is access to a curated resource repository that is valuable. 

Teacherbot is positioned as a research initiative that seeks new ways of understanding and developing automated teaching through adopting a critical posthumanist perspective.  While arguing for a critical posthumanist approach Bayne reviewed a previous initiative for automating teaching that was funded by the ESRC http://www.tel.ac.uk highlighting efficiency and productivity as the dominant discourse for that program. However, that section of the Bayne article mystified me. A closer look at the title of one of the targeted articles[1] offers a very different interpretation; higher quality and more effective learning are the outcomes that were envisioned. Nevertheless, Bayne develops a narrative that characterises the current conversation about automated teaching as dispute, with efficiency gains and teacher resistance oppositional views that need to be resolved. By response teacherbot is positioned as  ‘an assemblage of the human and non-human’ unhindered by humanistic assumption and efficiency agendas and thereby provides a new way of revisiting teacher automation.

Does teacherbot make a research contribution? The article is eloquently written and intriguing to read. However, the outcomes are mainly descriptive and anecdotal. As a teacher (and on occasion student) continuously and actively involved in online teaching and learning for more than two decades I have never considered the automation of teaching to be a threat.  Indeed, I can envisage how automation (for example, the collection and collation of learning analytics (LA) data) has promise and I would not object to it being considered as co-teaching provided that the automated information and myself were appropriately assembled so that LA information is monitored throughout.  However, I cannot discern any evidence to suggest that botty and the MOOC teaching team are entangled in a way that merits a claim of co-teaching or that this initiative has informed the scholarship of online teaching in any useful way. Furthermore,  the evidence presents botty as not very accomplished when it comes to recognising and responding to the socio-emotional needs of students – perhaps because it is not human.

1.         Laurillard, D., Productivity: Achieving higher quality and more effective learning in affrodable and acceptable ways. 2011.

http://www.tlrp.org/docs/ProdBeta.pdf.

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