Techno-science products for Education. What is on the horizon?

Schools are bombarded with products and courses that claim to be informed by research in Neuroscience and/or Digital Technology. Despite warnings from the OECD, the Royal Society (UK), the Wellcome Trust (UK) and Deans for Impact (USA), about the over extrapolation of science it is unsurprising that schools ‘buy into’ these products. A web of interrelated influences is determining how schools make spending decisions: government’s unrelenting pressure for school improvement, government’s adulation of techno-science (as a driver of the economy), the marketing might of the techno-science industry, the media’s tendency to hype innovation claims.

Affective Computing is one techno-science product that will arrive in the education marketplace. In the life world we express emotion, and interpret emotion in others, in a variety of ways. Affective Computing technologies are machines programmed to collect and interpret that information. The HE Horizon report for 2016 has just been published and it predicts a time to adoption of 4-5 years. The Horizon reports are collaboration between the New Media Consortium and the EDUCAUSE Learning Initiative (HE), Consortium for School Networking (K12) and are a useful source for a history of techno-science in education (1). Reports have been produced yearly, for Higher Education since 2004 and from 2009 for K-12. Each report draws on the expertise of a large international community of experts who collectively identify six emerging technologies for potential impact on Education, two within 1 year, two within 2-3 years, and two within 4-5 years. In general Horizon predictions: ubiquitous wireless in 2005, social networking in 2007, mobiles and cloud computing in 2009, electronic books in 2011, tablet computing in 2013, have been realised.  K12 has mostly mirrored the HE sector albeit with a lag of up to three years.

Technology forecasts made in the Horizon reports deserve attention before their arrival in the educational marketplace. Education has undoubtedly benefited for example, adult part time distance education students who use technologies such as mobiles and forums for discussion and collaborative activities with peers, from a place and at a time that is convenient. These technologies allow institutions to offer pedagogy that was not previously available to Distance Education. By contrast, virtual worlds have been much less successful. Second Life (SL), a commercially owned platform that provides users with facilities for constructing virtual objects and a virtual representation of self (avatar) was launched in 2003.  Most HE institutions in the UK invested financially in SL estate however; by 2011 it was largely abandoned by Education. SL was trumpeted as a superior online context when compared with text based forums.  The key claim, that it provided an immersive online experience, drew on ideas about ‘embodiment’ (neuroscience) and  ‘presence’ (communication) that were uncritically translated to learning contexts.

Emerging technologies such as SL tend to attract journal special issues and dedicated conferences yet critique of their educational value is sub-optimal. For example, Stanford University will host the first conference on ‘wearables for learning’ in November 2016 (2) Wearable technologies are incorporated into jewellery, clothing, footwear and were first listed as an emerging technology in the 2013 Horizon report. In the call for submissions the 19 topics are more focused on how to develop and introduce wearables to education than why the technology may be of value. Educational products that work best are those that target a problem already identified by practitioners for example, being able to offer a socio-cultural pedagogy to students studying at distance, the sophisticated video software from IRIS so that teachers can appraise and discuss real life practice and student behaviours with colleagues (3).

What are the educational problems that Affective Computing could address? Affect is not a constant and a practical strength of Affective Computing is its monitoring capability. However, a major limitation is that Affective Computing requires a computer mediated learning context for example: a VLE, an intelligent tutoring system, wearables. Affective Computing relies on data collected by other digital technologies, a case of a technological development being determined by the availability of other technologies. There are other issues; the ethics of quantifying the student, the validity of the physiological data collected, and the substantial question of how to theorize affect. A techno-scientific solution for mental health needs in the form of Affective Computing would be attractive to policy makers but is Affective Computing technology fit for purpose? To avoid being passive receivers educational researchers and practitioners need to infiltrate the specialised journals and technology conferences to challenge motivations and critique the value of these products for practice.

1 http://www.nmc.org/nmc-horizon/

2 http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=55214&copyownerid=46939

3 http://www.irisconnect.co.uk

What has the placebo effect got to do with Education?

Last night I attended the Biennial Kass lecture entitled “On the Efficacy of Placebos’. It was given by Charles Rosenberg. Professor of the History of Science (Emeritus) at Harvard.  I am getting involved with the History of Science, Technology and Medicine so as to become familiar with different ways of knowing and thinking, as a way to distance myself from disciplinary thinking in Education and Neuroscience and thereby gain another perspective for critiquing popular or accepted wisdoms. Rosenberg began by providing a definition of placebo ‘ a label for a shallow momentary effect’ and described how it was discussed in History; as a distractor in the eighteenth century, the patient wanting something in the nineteenth century while our modern day Wikipedia describes it as a form of deceit.

For medicine it is generally assumed that a placebo lacks efficacy and that is why it is given in many randomised clinical trials of treatment effects. Rosenberg raised a challenging question about this assumption.  Is it the case that a placebo is inert/ineffective? Or is the act of receiving a placebo from the doctor the active ingredient?

A similar question could be raised in Education. Lets assume that any intervention based on a neuromyth has the status of a placebo. What if a neuromyth for example, teaching according to a student’s learning style preference, has transactional efficacy? Although irrelevant neuroscientifically it has relevance for the student and therefore works for them, it provides a structure of choice for the student Also, the active ingredient could be in the interaction dynamics between the student and the teacher. There is also the question of whether the intervention has its placebo effect on the teacher who provides it.  It is an idea that may explain why teaching to learning style has become embedded in educational culture as a ‘good’ thing.

A multi-disciplinary conversation about Collective intelligence – reflection on some missing elements

The mobile phone and its connectivity with the internet allows growing numbers of us to find, connect, and interact. That was the technological foundation for the original vision of cMOOCs (developed by George Siemens and Stephen Downes) as a democratic learning experience, and connectivism as a learning theory for a digital age (Siemens 2005).

Collectivism, as discussed in a multi disciplinary context at Nesta http://www.nesta.org.uk/event/roots-collective-intelligence, relies on the same technological infrastructure. What is collectivism and how does it differ from connectivism? We heard that the Internet allows for a new form of activism for example, political. How do individuals participate? We were given the example of number of Facebook likes as an indicator of collective intentionality, a starting point. However, how to sustain collectivism i.e. participation, was a recurrent question; how does an individual move on from the Facebook click to participate?  Participating in connectivist learning opportunities requires good infrastructure design and from the individual curiosity, motivation to learn, to contribute, openness, digital literacy (a fair amount) and I would argue that digital fluency and socio-emotional experience are the elements that sustain on-going participation.

Intelligence. Summing up the day Colin Blakemore focused on intelligence. His considered opinion was that we hadn’t spent enough time talking about what we meant by intelligence. He is a cognitive neuroscience and so unsurprisingly, he also spent some time reflecting on the contributions made by the speakers who were cognitive scientists. Those mainly cohered around what, when and how collective intelligence occurs with when and what depending on group size (Robin Dunbar) how on noise reduction, competence, persistence, reputation (Chris Frith). Others concentrated on decision making as investigated in the laboratory; the role of argumentation in decision-making and the quality of decision making. This was a useful contribution as we had already heard that a binary response as the norm could be the problem for collectivism in political contexts. Also, it has some connection with learning science, where design for collaborative learning (i.e. group work) requires a joint task and the opportunity to propose ideas, discuss them with others, negotiate a solution to disparate ideas, and contribute to a shared outcome.

Overall, the multi-disciplinary approach was very successful. However, there was a sense that the individual was objectified. The subjective was largely missing from the day; purposefulness and socio-emotional experience. Therefore, it was interesting to learn about the fall off in Wikipedia contributions since bots were introduced. The explanation provided was that the bots were overly obedient to protocol and rules - another example of the clunkiness of bot interaction as described in a previous post and that the uniquely human nature of socio-emotional experience is so often neglected

Surely, design is important both for successful knowledge building and the socio-emotional experience of collective action.

Siemens, G. (2005). Connectivism: A learning theory for a digital age. International journal of instructional technology and distance learning, 2(1), 3-38.

Spending a day with the Emotion Historians

This event https://emotionsblog.history.qmul.ac.uk/2015/09/tears-and-smiles-programme/ was an opportunity to exercise some transdisciplinary thinking. Could emotion historians contribute to the scholarship of online and distance education?  Specifically, the issue of disembodiment when interpersonal interaction takes place online.

Descriptors assigning purpose to an emotion (e.g. mocking, patronising) peppered the day and emotion as culturally situated performance for control, or to resist control, was a strong theme to emerge. Emotion as a rational act expressed for strategic purposes although, there was some debate on ‘the complex emotion repertoire’ of Margery Kempe (a medieval mystic). While those around Kempe  perceived her behaviour as irrational it could be explained as a manifestation of illness. Self-report by Kempe, that sensory stimuli could  trigger strong emotion, would fit with the experience of some with neural evidence of temporal lobe epilepsy. 

Emotion as experienced and in particular socio-emotional experience, those feelings and thoughts embedded in the dynamic of an interpersonal interaction, did not feature. Understanding social emotions is important for a socio-cultural pedagogy based on the idea that students will co-construct knowledge through discussion, through sharing ideas. The negotiation of ideas can generate strong emotions and when it takes place online it is through written communication and is mediated by a digital device i.e. the physical other is unseen. ‘The textual face of the medieval poet’ did provide an eloquent account of using literary device such as metaphor and the multimodal  (through styling for example, embolden) to express emotion and achieve emphasis through writing  (as is the case when people interact online).  But once again, this account was confined to the expression of emotion and one-way interaction i.e. poet to reader.

Art history provided considerable resource throughout the day, an observer interpretation of an expressed emotion that is then reinterpreted by the historian.    By contrast social emotions rely on language,  spoken or written, and their history would require a different resource. So, while I enjoyed an illuminating set of talks, thank you, I am still searching for the history of those emotions, experienced and expressed, that are embedded in the social.

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.