The Place of Tech in Ed Tech

This is a follow-up, or another view relevant to my last post. George Siemens posted this goodbye to his involvement in Ed Tech because:

(E)ducational technology is not becoming more human; it is making the human a technology. Instead of improving teaching and learning, today’s technology re-writes teaching and learning to function according to a very narrow spectrum of single, de-contextualized skills. . . . (Ed Tech programs) require the human, the learner, to become a technology, to become a component within their well-architected software system. Sit and click. Sit and click. So much of learning involves decision making, developing meta-cognitive skills, exploring, finding passion, taking peripheral paths. Automation treats the person as an object to which things are done. There is no reason to think, no reason to go through the valuable confusion process of learning, no need to be a human. Simply consume. Simply consume. Click and be knowledgeable.

2 pointsOne, this is partially the result of Tech without ontology and an appropriate teleology. There is no question that Ed Tech is more efficient at whatever it is doing, but without specifying an ontology, it’s really not possible to know what it is doing. This was an underlying problem with Behaviorism. Behaviors were being changed but without a framework that would clue you in to the “what”, “why” and to “what end”. This is why so much Ed Tech is no more than a more complex Skinnerian teaching machine.

Second point, Tech can be used as a more efficient substitute for a human in simple transactional interactions, (think ATMs, self-checkout lines or checking your flight status) but not in systems that are highly variable (Try getting software or customer support help from an automated system. It’s usually a disaster.) Simple decontextualized skill acquisition is an important part of education, but only a small part. Current Ed Tech is good for memorizing math facts, increasing reading levels or memorizing basic decontextualized domain facts, but the hope for education is for much more. Ed Tech is striving to do more, but here are 3 aspects where I believe Ed Tech is not near to being a substitute for a teacher:

  1. Fostering creativity. This is advanced language use (including math) to evaluate and synthesize knowledge and to reach new combinations, new uses and new ideas.
  2. Engaging in social practices. Most of what we do is not to just use knowledge, but to engage with practices that we share with other people, or as Wittgenstein put it; to engage in language games. These are things that even deep AI cannot come close to imitating.
  3. Develop meaningful networks and connections with other people. This may be the most important ability in the future and the only way it can be learned is in direct engagement with other people.

I believe that Technology can help in these areas, not as a substitute for teachers, but by fostering new affordances for teachers which is an intense pedagogical research project and will require new tech from what I’ve seen so far. As an example consider the text editor. Conceived as a replacement for hand writing or the typewriter, it allows new affordances like email, blog posts, spelling and grammar checking or language translation. All these things extend human capabilities, but cannot substitute for it. Ed Tech will require teachers to become more capable and knowledgable with advanced pedagogy and it will make teachers more efficient but only if it creates new affordances for teachers. It must recognizes and constitute a new pedagogical framework that centers on the teacher and the teacher student diode.

Responsible and Principled Ed Tech Design:The Need for Ontology and Teleology

It’s being said that the future of education is machine centered and algorithmic, and the greatest critique of this vision centers on a lack of transparency. ( Waters and Williamson). If we want to understand the impact of Ed Tech and Big Data, as well as to shape our own future, we should start with clarity; a clear eyed view of who we are, who we want to be and the pedagogical processes to get there. That is, let’s specify the ontology (who is an educated person) and the teleology (developmental pedagogical processes) of principled and well-structured Ed Tech information systems designed to serve the educational needs of networked people in dialogic relations.

An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them.  . . .   There is no one correct way to model a domain— there are always viable alternatives. The best solution almost always depends on the application that you have in mind. (Noy & McGuiness, )

This ontology should reflect evidence-based competencies, not just the parroting of knowledge.

When higher level skill sets are the real objects of measurement, it is necessary to evaluate assessment activities not by their surface similarities with learning domains but by their deep structural correspondences with intended learning outcomes; . . . To ensure that assessment activities yield useful data for making inferences about student learning beyond simple knowledge claims, principled assessment design must guide the development and structure of the assessment. Principled assessment design can be viewed as a plan, comprising a visual or textual scheme, to guide the purpose, expression, development, internal structure, and defensibility of an assessment. (Shute et. al. 2014)

If we don’t achieve specificity, algorithm designers will continue to do it for us in opaque and thoughtless ways. I believe that transparency problems can exist not only because of interference with corporate interest as Dr Williamson implies. but also because of a lack of clarity in principled system design. Specifying the underlying ontology and teleology of Ed Tech and Big Data Systems will go a long way to improving this situation.

For further clarification, ontology in machine learning can be seen as different from ontology in philosophy, but when we look at these applications as educational processes, we need to look well beyond the code. A common refrain in Ed tech is that the field is populated by programmers with little understanding of the history and concepts of education. This is to say that programmers think of ontologies and applications as limited to the current program code, but educational applications should reflect networked people in dialogue. In defining a common vocabulary, an ontology’s domain should support students, student development, and the the educational process. This aspect forms the core  ontological commitments that allow a model of the domain to be created in a way that is meaningful across the domain for teachers technologists and students. This ontology is also important for interpreting the analysis and applying the data analysis to the process of educational and personal student development. Without an interpretation that also reflects ontological commitments it can’t fully communicated and implemented in the kind of educational practices we expect today.

(T)he goal of data collection and analysis is to provide insight and inform decisions. Accordingly, there is a long chain of reasoning that needs to be considered.” We recognize that data is a representation of the world and like all representations, it is an imperfect system which will not perfectly capture the detail of the world. We also believe that all of the activity coming after that (analysis, interpretation, etc.) is a human endeavor, involving all the benefits and challenges that implies. (Kristen DiCerbo, Pearson)

DiCerbo provides a chain of reasoning that lacks an ontology and teleology. “Big Date” in this view is not based on a principled assessment design. What will result is much more than an imperfect reflection of the world, but an opaque data system. What we need is more than people with knowledge on the inside. What we need is principled assessment design backed up by principled system design. More than just trust, more than just efficiency, we need systems that are worthy of guiding educational teleology.