Category Archives: LRNT 523

Educational Technology in 2030: AI Driven Chatbots as Teacher’s Assistants

In the year 2030, higher education institutions will continue to grow in both faculty and student populations.  The increased hiring of part-time faculty over full-time in those institutions will force them into a position where they will have to rely on technological intervention to provide their students with engaging and valuable learning experiences.  Chatbots, software applications that allow for simulated conversations with users on the internet, will fill in the gaps where educators are unavailable to communicate and will record interactions with students to develop learning profiles.

It has been the trend in the past ten years to hire part-time faculty in greater numbers than full-time and there is little reason to believe the hiring patterns will change in the next ten.  There are a number of reasons that support the decision to hire part-time faculty.  Wyles (1998) observed the many benefits part-time faculty bring to their educational institutions, including reduced cost, flexibility in course delivery, and a continued connection to industry knowledge and practices (pp. 89, 92).  In addition, there appears to be no distinction between the quality of education provided by part-time faculty when compared to full-time.  Rogers (2015) asserted that students were not negatively impacted by the teaching practices of part-time faculty and that there appeared to be little support for the argument to increase full-time hiring to increase learning outcomes for students (p. 682).  These benefits are unlikely to shift within the next ten years.  On the contrary, observing the hiring practices of one Canadian practical college, as represented in Figure 1, the trend towards hiring part-time faculty over full-time is increasing, showing a greater divide between the two designations.  Since part-time faculty are limited in the number of course hours they are permitted to teach, the volume of educators employed at educational institutions is likely to increase by the year 2030.  At the same time, the number of students for which each educator is responsible, is also increasing.  Eicher et al. (2018) noted during the implementation of an Artificial Intelligence (AI) as a teacher’s assistant, that the growing number of students in their online course had grown to a size where interactions with students by humans was becoming unmanageable (p. 88).  As a result, it is likely that an increasingly part-time faculty will require additional technical assistance in the future.

Figure 1

Fanshawe College Faculty Distribution

Note. This figure represents the categories of faculty employed at Fanshawe College between 2012 and 2019.  Part-time and Partial Load are both considered part-time faculty and are combined as Total Part-time.  Full-time and Sessional are both considered full-time faculty are combined as Total Full-Time. a) Data was acquired from the OPSEU Local 110 October College Staffing Survey available at b) Data for the 2013 academic year was unavailable and is not represented here.

In order to keep the cost of human resources to a minimum, educational institutions will increasingly rely on technological interventions to support educators.  Chatbots powered by AI are a likely candidate to act as a teacher’s assistant for faculty, allowing them to focus their time effectively.  To begin with, there could be concerns that interacting with a machine rather than a human teacher could reduce student engagement.  Crutzen et al. (2011) indicated that students would react positively to communicating with a chatbot (p. 519).  If students enjoy their interactions with a chatbot, they will be more likely to make use of it when they need questions answered when the teacher is not available.  Smutny and Schreiberova (2020) demonstrated that chatbots are instantly available and can provide students with assistance while communicating with them in a conversational manner (p. 2).  In this way, students need not wait for a response from an unavailable educator and can continue to work on their studies on their own time, increasing the accessibility of their education.  Additionally, the use of chatbots could increase course participation by alleviating the anxiety of some students.  Burke (2019) suggested that some students avoid asking teachers questions due to a fear of being ridiculed or judged and that the use of a system that provided them with an opportunity to engage in class anonymously increased their participation.  At the same time, Crutzen et al. (2011) showed that adolescents perceived chatbots as both faster and more anonymous than information lines and search engines (p. 518).  These two facts combined; an environment of perceived anonymity, and an increase in participation under that condition; suggests that students would be more engaged in a course with the usage of chatbots as a teacher’s assistant.

Another positive outcome of the use of chatbots as teachers’ assistants would be the ability to gather data on student interactions to be used for developing personalized learning.  By the year 2030, it is very likely that students will be accessing their virtual learning environment on a number of devices such as their computer, mobile device, and even wearable technology such as a smart watch.  Those devices would not only be used to gather information on students’ interactions with the chatbot, but physiological data would also be recorded to be used to determine their emotional state.  Knox (2020) argued that wearable technology could be used to capture physiological data including facial expressions, neurological responses, and heart rate amongst others to determine an individual’s feelings to identify at risk students, which could then be used to modify their behaviour (pp. 35, 39).  The information gathered could be used to inform the chatbot’s interactions with the student in order to provide subtle suggestions that would gradually shift their behaviour in a direction which would be more conducive to their academic success.  This will only be the beginning as AI becomes more efficient with data usage and can make analyses with less information.  Sucholutsky and Schonlau (2020) have provided evidence that AI can be used to infer accurate conclusions based on an extremely limited amount of data.  As the efficiency of machine learning accelerates, it will be possible for AI powered chatbots to come to conclusions about students’ performance and emotional states without having to be exposed to all of the data currently required.  By 2030, it is feasible to believe that this technology will have advanced sufficiently to have a significant impact in education.

In conclusion, it is likely that educational institutions will continue the trend of hiring part-time faculty over full-time, significantly increasing the size of their teaching staff. At the same time, the student populations will also increase, and educators will be responsible for increasingly large class sizes.  As a result, those institutions will be forced into a position, as a cost saving measure, to employ AI powered chatbots to maintain, or even improve, the student learning experience.


Burke, L. (2019). Behind the Back Channel: Can Giving Students Anonymity Help Them Engage In Class? Inside Higher Ed.

Crutzen, R., Peters, G. J. Y., Portugal, S. D., Fisser, E. M., & Grolleman, J. J. (2011). An artificially intelligent chat agent that answers adolescents’ questions related to sex, drugs, and alcohol: An exploratory study. Journal of Adolescent Health, 48(5), 514–519.

Eicher, B., Polepeddi, L., & Goel, A. (2018). Jill Watson Doesn’t Care if You’re Pregnant: Grounding AI Ethics in Empirical Studies. AIES 2018 – Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 88–94.

Knox, J., Williamson, B., & Bayne, S. (2020). Machine behaviourism: future visions of ‘learnification’ and ‘datafication’ across humans and digital technologies. Learning, Media and Technology, 45(1), 31–45.

Rogers, G. S. (2015). Part-time faculty and community college student success. Community College Journal of Research and Practice, 39(7), 673–684.

Smutny, P., & Schreiberova, P. (2020). Chatbots for learning: A review of educational chatbots for the Facebook Messenger. Computers and Education, 151(February), 1-11.

Sucholutsky, I., & Schonlau, M. (2020). ’Less Than One’-Shot Learning: Learning N Classes From M<N Samples.

Wyles, B. A. (1998). Adjunct faculty in the community college: realities and challenges. New Directions for Higher Education, 104, 89-93.

Opportunity or Oppression?

Take My Hand – Photo by Photos Hobby on Unsplash

A Frightfully Optimistic Future

This week I spent some time reading two articles making speculations about the future of technology’s impact on education.  In both articles there was a mix of optimism and pessimism.  I think the above photograph does a good job of expressing how the readings made me feel.  The title of the photo is “Take My Hand”, suggesting the photographer saw the robot as a helpful tool, or even a leader.  At the same time, the robot’s balled up fist calls into question the robot’s intentions and one can’t help but wonder what type of leader it would be.  So, will educational technology turn out to be the provider of opportunity or oppression?


Macgilchrist et al. (2020) presented three possible futures with speculations ranging from dystopian to hopeful.  In the third scenario, the most optimistic, the authors predicted the democratization of information and the eventual personal ownership of private data.  They described a revolution of sorts which includes a shift in control over information from corporate entities to decentralization in the form of open source technologies and educational resources (p. 86).  This is an exciting future, which has an opportunity to reduce inequality and open doors previously closed to many.  Realistic, though?  I’m not sure.


Selwyn et al. (2020) presented a series of vignettes which expressed a considerably darker version of the future of educational technology.  The story that really caught my attention was Vignette #5, describing an Orwellian educational environment in which students’ thoughts and emotions are constantly monitored and evaluated.  While I think the idea that, in 10 years’ time, students will be lightly shocked in order to maintain their attention in class is a little far fetched, the idea that artificial intelligence could monitor students’ emotions and make judgements isn’t unrealistic (p. 100).  How we use those tools in the future could be incredibly beneficial, or equally likely, could lead to an unfortunate fate at the wrong end of a menacing robotic fist.


Macgilchrist, F., Allert, H., & Bruch, A. (2020). Students and society in the 2020s.  Three future ‘histories’ of education and technology. Learning, Media and Technology, 45(1), 75-89. DOI: 10.1080/17439884.2019.1656235.

Selwyn, N., Pangrazio, L., Nemorin, S., & Perrotta, C. (2020). What might the school of 2030 be like? An exercise in social science fiction. Learning, Media and Technology, 45(1), 90-106.

Techno-Determinism in Education

Photo by Thomas Park on Unsplash
By Denys Koval & Christopher Rowe

Over the past week, we’ve been exploring a disagreement in the EdTech world known as the Great Media Debate.  In the late 80’s and early 90’s, Richard E. Clark and Robert B. Kozma separately authored a series of articles presenting their opposing views on the issue of whether or not media has an impact on learning.  Clark’s (1994) position was that media was simply a delivery tool for learning methods and while necessary, could be replaced with a media with overlapping attributes that performed similar cognitive functions (pp. 22, 26).  Kozma (1994), on the other hand, believed that the specific cluster of attributes associated with a medium, presented opportunities for employing unique learning methods (pp. 13-14).  These opposing views continue to influence how educational technologists introduce new tech into a learning environment.  With this debate in mind, we’ve found two contemporary articles discussing the use of technology in the classroom and considered how both Clark and Kozma would respond to them.


Zoë Bernard (2017), tech reporter for Business Insider magazine, wrote an article titled Here’s how technology is shaping the future of education, focusing on how technology is increasingly providing educators with the ability to assess their students on an individual level, and thereby tailor lesson plans to suite their unique needs.  She pointed to developments in the EdTech industry which have increased the accessibility of this strategy.   Kozma and Clark would have interpreted Bernard’s article differently, to be certain.  They would have neither agreed on the proper implementation of the new technology mentioned in the article, nor on the method of its development.

Bernard described how the increased availability of adaptive learning software such as DreamBox, which can monitor an individual student’s progress and provide the appropriate curriculum for their skill level, is allowing educators to work with learners at a pace set by the student. If presented with software like DreamBox, Kozma might argue that the availability of this new technology would provide educators with an opportunity to develop new teaching methods to best take advantage of its unique characteristics.  Kozma (1994) asserted that theories to direct the use of media in instructional design should consider both the unique capabilities of media, but also the “complexities of the social situations with which they are used” (p. 15).  Classrooms are indeed social environments.  If we change the social environment of the classroom, by tailoring the experience to meet the needs of the individual, Kozma would likely say that we must develop new teaching methods designed specifically for the unique cluster of attributes presented by the media forcing that change.  In contrast, Clark might argue that it was always possible for an educator to learn about the progress of an individual student and tailor learning plans to meet their needs, but that this software makes the teacher’s ability to do that more efficient.  Clark (1994) insisted that “the methods used in CBI [computer-based instruction] can be and are used by teachers in live instruction” (p.24).  He believed that teaching methods and the media used to deliver them are separate and that various media could be used to achieve the same goal.  The difference, he claimed, in the way that various media impact learning, is the efficiency with which a particular media might achieve learning outcomes (p. 22).

In her article, Bernard (2017) included a quote from DreamBox’s senior vice-president of learning, Tim Hudson, who expressed that “it’s important that we listen to teachers and administrators to determine the ways technology can assist them in the classroom.”  While Kozma and Clark likely would have both approved of Hudson’s insistence on communicating with educators in the development of new tools, chances are they would disagree on how that communication should take place.  Kozma would likely have been interested in seeing what technology had been developed, so that he could create effective teaching methods based on whatever new capabilities that technology presents.  He argued that while the implementation of a specific technology would limit the options available to educators, the capabilities of that media would also provide direction on what could be accomplished with it (Kozma, 1994, p. 20).  Clark, on the other hand, would probably have approached software developers looking for the technology that would most efficiently facilitate a specific teaching method he already had in mind.  It was Clark’s (1994) position that “it is important to derive media that are capable of delivering the method at the least expensive rate and in the speediest fashion” (p. 26).  From his perspective, it would be the teaching method that should dictate the choice of a technology.

Socially Accessible

Celano, the author of the article Technology in the classroom: How educators are using remote technology as they return to school, published on Owl Labs’ website, references NBC News Correspondent Kerry Sanders, who reported that due to Covid-19, about 30% of the kids from Charter School USA stopped learning due to the lack of engagement between teachers and their students. Owl Labs then promotes the Meeting Owl as a solution for a virtual classroom, emphasizing its 360° camera, which allows educators to teach as they normally would by treating their virtual classroom as a physical one, therefore allowing remote students to stay engaged.

Clark might argue that while the Meeting Owl increases the accessibility of the learning method that the teacher is employing, while it cannot be directly responsible for motivating learning. He would cite Salomon and others “who draw on the new cognitive theories which attribute motivation to learners’ beliefs and expectations about their reactions to external events – not to external events alone” (Clark, 1994, p. 23).

Kozma might argue that Meeting Owl can be responsible for increasing the motivation to learn by making students feel like they are a part of a social process, which is achieved by facilitating interaction with physical resources as well as other students in the classroom. “Learning is not the receptive response to instruction’s “delivery”. Rather, learning is an active, constructive, cognitive and social process by which the learner strategically manages available cognitive, physical, and social resources to create new knowledge by interacting with information in the environment” (Kozma, 1994, p. 3).


Bernard, Z. (2017, December 27). Here’s how technology is shaping the future of education. Business Insider.

Celano, K. (2020). Technology in the Classroom: How Educators are Using Remote Technology as They Return to School. Owl Labs.

Clark, R.E. (1994). Media will never influence learning. Educational Technology Research and Development, 42(2), 21-29.

Kozma, R.B. (1994). Will media influence learning? Reframing the debate. Educational Technology Research and Development, 42(2), 7-19.

Derek Bruff – Providing a Voice

Photo by Jason Rosewell on Unsplash

An Influencer in Educational Technology

I’ve recently been tasked with providing a little background on an influential player in the educational technology field.  After some investigating, an individual came to my attention who has had both a significant impact on ed tech in his own right, but has also provided a platform for others to spread their reach.  The gentleman in question is Dr. Derek Bruff, Director of the Center for Teaching and Senior Lecturer in Mathematics at Vanderbilt University.  In his capacity as the Director for the Center of Teaching, Bruff looks to provide practical applications for the use of ed tech by faculty in higher education, and in so doing, he’s been quite prolific.  He posts regularly to his blog (Agile Learning), has published two books (Teaching with Classroom Response Systems: Creating Active Learning Environments and Intentional Tech: Principles to Guide the Use of Educational Technology in College Teaching), has authored a long list of cited publications.

What interests me most, however, is his podcast, Leading Lines.  Produced at Vanderbilt University, Bruff acts as host and interviews a wide range of educators, discussing the application of technology in education.  It’s with this tool that Bruff provides a platform for passionate, skilled, and creative educators representing a diverse selection of perspectives.  Episodes are released on a rough, bi-weekly schedule and focus on first hand experiences with tech and students.

I’ve subscribed to the podcast.  I recommend you do the same!

Reflection on 25 Years of Ed Tech – Chapters 9 – 18

Sedimentation – Photo by Paul Van Cotthem on Unsplash

Software Sedimentation (Alignment with Current Practice)

One concept that Weller presented in his book that resonated with me is that of software sedimentation (Lanier, 2002, as cited in Weller, 2020, p. 65).  The idea is that a piece of software becomes so entrenched in the way an institution operates, it becomes extremely difficult to move away from it.  In the program that I teach in, we suffer significantly from this sedimentation.  In one specific instance, we use a particular program to schedule the music for our radio station called Selector.  It’s an old DOS based program that functions adequately and does a decent job of presenting scheduling techniques to our students.  It is, however, without question, outdated.  Not only do we know of better programs, we actually have the license for one; a program called MusicMaster.  The issue is that the amount of labour that would be involved in replacing the old system with the new one is so significant that it seems insurmountable.  I don’t have a solution to recommend for this problem, but I suppose the first issue is to recognize there’s a problem in the first place.

Celebration of Failure (A Conflict with Current Practice)

As I continue to read through Weller’s book, I’m beginning to recognize a recurring theme; one of failed attempts to develop mainstream technology adoption in education.  Many chapters tell the tale of grand innovations that were popular with a short period before fizzling out.  What comes to my attention is the commonality in the reasons for the failures.

    • High Overhead (too much work input… not enough return)
      • Learning Objects – Metadata
      • Personal Learning Environments – Customization
      • E-Portfolios – Lack of support from institution
    • Definition Debates (Lack of consensus)
      • Learning Objects
      • Social Objects

One thing we don’t appear to be good at, is celebrating our failures.  New technology that doesn’t reach a certain threshold of adoption into the mainstream, disappears quietly into the night… as opposed to benefitting from a celebratory examination of the failure to harvest what lessons we can to apply them to future projects.  As a result, similar to my previous post on the first eight chapters of this book, we’re condemned to repeat our mistakes.  In a TED (2016) video, Google X’s Captain of Moonshots, Astro Teller, described how they have long employed the philosophy of celebrating failure, which has allowed them to tackle seemingly impossible tasks with some success (13:40).  I find that in the college system, we play lip service to this idea.  We regularly tout the idea that failure is the great educator, but seldomly do we put the concept into practice.  If we could be more vocal about celebrating our failures and exploring the lessons to be learned from them, we would be less likely to repeat the same mistakes in the future.


TED. (2016, May 9). Astro Teller: The unexpected benefit of celebrating failure [Video file]. YouTube.

Weller, M. (2020). 25 years of ed tech. Athabasca University Press.

Reflection on 25 Years of Ed Tech – Chapters 1 – 8

Repetition – Photo by Matthew T Rader on Unsplash

I’ve been reading Martin Weller’s book titled, 25 Years of Ed Tech.  It’s an historical recounting of Weller’s experience as a professor of educational technology at Open University in the UK with the development of ed tech over a twenty-five year period beginning in 1994.

Was 1994 the appropriate year to start with?

I think so.  The book that Weller set out to write is a history of how web based digital technology has had an impact on education, not a history on educational technology in general.  Certainly, educational technology was in use prior to 1994 and took many forms, but in order for this book to be focused and concise, Weller would have had to make a decision on what to include and when to begin.  Lunduke (2017) indicated that Bulletin Board Systems (BBS), the topic of the first chapter of 25 Years of Ed Tech, had been in use since the eighties.  Having said that, Weller (2020) admitted in the introduction of his book that he’s “guilty of… being rather arbitrary in allocating a specific year to any given technology“ (p. 6).  The book had to begin somewhere, and the transition between BBS and the web was certainly a pivotal moment into the era which is the central theme of this history.  So, this seems like a logical place to start.

Reactions to Weller’s Writing

One of main themes of Weller’s (2020) book that has so far stood out to me is the “historical amnesia of educational technology” (p. 11).   This concept reinforces Santayana’s (1905/2017) frequently misquoted passage, “those who cannot remember the past are condemned to repeat it” (p. 132).  This theme was most obviously illustrated to me when Weller outlined Carr-Chellman and Duschatel’s (2000, as cited in Weller, 2020) application of constructivism theory in the development of the ideal online course.  The list of recommended components are so familiar…

    • An online study guide
    • No online textbook
    • Assignments
    • Examples of previous student’s work
    • Student-to-student communication
    • Interactive skill building

This list holds up so well, despite being twenty years old and created in the infancy of online learning, and yet I feel like those who are developing online courses for the first time in the post COVID-19 educational environment, are discovering these concepts for the first time as though they were new.


Lunduke, B. (August 28, 2017). History of computers, part 1 – The bulletin board system. Network World.

Santayana, G. (2017). The life of reason. ProQuest Ebook Central. (Original work published 1905)

Weller, M. (2020). 25 years of ed tech. Athabasca University Press.