IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

Post-COVID-19 Higher Learning: Towards Telagogy, A Web-Based
Learning Experience
Teboho Pitso
Vaal University of Technology, South Africa

39

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

Abstract
Institutes of higher education (IHEs) have to consider benefits of remote learning postpandemic. Retrogression to physical contact is counterproductive. The hasty implementationof remote learning during the pandemic deprived IHEs of opportunities to efficiently enact andtheorise about it. Post-pandemic, IHEs have opportunities to theorise about remote learning
hence the questions; a) what type of learning emerges when asynchronous and technology-asessence framework undergirds students learning? b) What benefits accrue when chatGenerative Pre-training Transformer (chat-GPT) is infused into students learning? Use ofsynchronous learning and technology-as-utility framework to underpin remote learning during
the pandemic was intended to retain most of physical contact learning traditions. Teachers andstudents met synchronously and simultaneously online for learning to occur. IHEs safeguarded
their operational efficiency to minimise the disruptive nature of remote learning. The purposeof the study was to theoretically examine effects of asynchronous learning and “technologyas-essence framework on students learning. Asynchronous learning occurs when students
registered on the same course learn online on their own schedule without any real-time
interactions with teachers. This phenomenon occurs when remote learning develops throughtechnological advances that, beyond 2030, would most likely stream educational courses
similar to Netflix. One such technological advance is chat-GPT. A study was undertaken tobetter understand it. 15 multi-disciplinary advanced undergraduates tested out chat-GPT on
their assignments and a concrete problem. Chat-GPT lessened the time of doing assignments
and improves students’ problem solving abilities. AI systems advances have a positive effecton students learning. The study addresses the positive impact of asynchronous learning andadvances in technology on IHEs.
Keywords: artificial intelligence, chat-GPT, remote learning, technology, Post-COVID-19
pandemic40

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

The post-pandemic era provides Institutes of Higher Education (IHEs) with opportunities toreimagine learning within the ambit of advanced remote learning. Remote learning refers to amode of learning that occurs online via scheduled Zoom classes and Bright-space activities
because in-person traditional classroom learning was not possible during the Covid-19
pandemic (Burke and Locmele, 2022; Neuwirth, 2021; Torres and Ortega-dela Cruz, 2022). It
thrives on synchronous learning where students and teachers meet in live online classes in order
for learning and teaching to take place. While occurring online, synchronous remote learning
tends to mimic in-person contact sessions. I argue that remote learning that assumes anasynchronous learning approach is likely to help IHEs to reimagine learning in the digital age.
An asynchronous approach refers to any mode of online learning undertaken at the behest of
students’ own schedule and has no need for live online interactions between students andteachers. It shares similarities with heutagogy (Blasche, 2012) where students access learning
content as and when they are ready to do so, at their own pace, anywhere and anytime. The
brick-and-mortar traditional classrooms are becoming increasingly outdated and would
struggle to survive outside online learning. The asynchronous student-centred learning
approach with a strong self-determination character that builds students’ capabilities to beautonomous, self-reliant, and technologically savvy represents a way forward for IHEs. I referto this type of online, web-based learning as telagogy. I also forecast that beyond 2030,
telagogy would become an asynchronous, online learning experience that would be streamed
like Netflix and controlled fully by students as Wright (2020) suggests. Telagogy would alsoenable students to curate their own personal curriculum drawing educational courses fromuniversities across the entire world. This would compel IHEs to develop universal accreditation
systems. It is these meanings of telagogy that make it an advanced form of remote learning. It
is anticipated that governments may consider funding students instead of universities.
Another crucial feature of telagogy would be to fundamentally shift the work of human teachers
away from textbooks and study guides towards new role demands. Sterling (2020) suggeststhat university teachers ought to stop trying to write down knowledge that is already available
in many AI systems such as chat-GPT and refocus their energies on how to better incorporate
these AI and advanced technology capabilities in student learning. Asynchronous approach tolearning, in particular, reconfigures human teachers’ role in advanced remote learning and iscritical in theorising about learning and teaching in the digital age. Options of asynchronous
learning for human teachers include posting, developing text or multimedia resources,
preparing online polls/quizzes, students’ contribution to collectively authored resources andco-creating educational course blogs, creating educational You-Tube videos (Buxton, 2014;
Watts, 2016; National Forum, 2020; Butler, 2020). Asynchronous online learning opens spaces
to determine future imaginings of remote learning that include online streaming of educationalcourses, digital accreditation of personal curricula of students, digital assessment, use of new
digital learning techniques such as chat-GPT. This would turn higher education into a diverse,interactive, open, engaging activity (Bayne et al, 2020) that fosters self-directed learning, peer
learning, and student agency (Blasche, 2012; Junco, 2010; Halupa, 2015). Assessment can bereimagined beyond text-based assessments to include audio-clips, videos with evidence ofpractical projects that solve community problems, animation, and image making (National
Forum, 2020). Another key consideration in seeking advanced remote learning features

41

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

includes virtual learning environments (VLEs) that have a proven record of use in online
learning particularly on content delivery, digital assessment, lecturer-student engagement, andbig data analytics (Anderson, 2016). However, VLEs are not without its critics. The platform
is seen as constraining pedagogical practices and undermining digital/web literacy practices(Williams, 2023; National forum, 2020). In this study, concerns about remote learning beyond
VLEs and synchronous offerings relate to how technology was viewed during the pandemic.
Two main approaches that guided the use of technology in IHEs during COVID-19 pandemic
were synchronous learning and technology-as-utility anthropological conception. As alreadystated, these two approaches restricted remote learning to operational efficiency rather thancreating conditions for new theorisations about learning and teaching. The implementation of
remote learning during the pandemic relied on synchronous, technology-as-utility framework.
The post-pandemic technological framework that is likely to help IHEs to reimagine student
learning would thus entail asynchronous, technology-as-essence framework (Heidegger, 1954;
1977 Translation) and is the focus of this study.
The purpose of the study is to better understand students’ learning post-pandemic undertechnological conditions of asynchronicity and technology-as-essence framework (Heidegger,
1954; 1977 Translation) that are key constructs in theorising telagogy as an advanced stage of
remote learning. Furthermore, the study seeks a qualitative enquiry of process of using one of
the latest AI systems called chat-GPT on students’ assignments and their attempts to resolve a
concrete problem. Two questions that framed the study were thus:••

What type of learning emerges when asynchronous and technology-as-essence
framework undergirds students’ learning?
What benefits accrue when chat-GPT is infused into students’ learning?

In the next section, the theoretical framework based in literature review is developed in orderto ground the systematic investigation undertaken to better understand students’ learning postpandemic. A conceptual framework that shows technological variables necessary to be infused
to shape students learning in the digital age follows the description of the theoreticalframework. The research that tested out chat-GPT for student learning is also described
including its methods, findings, and discussion.
Theoretical Framework
Theories for online learning such as that of Anderson’s Online Learning Model (Anderson, 2011)
and Picciano’s Integrated Online Learning Model (Picciano, 2017) have evolved over time.
These models tend to assume a pedagogical framing within a synchronous and technology-asutility framework. I argue that this theoretical conception of online learning would not lead toadvances in remote learning that could culminate in what I call telagogy, or streaming online
educational courses. Telagogy is understood as a method and practice of students’ web-basedlearning that draws from remote learning but goes beyond its pandemic conception assynchronous utility. Remote learning was conceptualised and implemented force majeure during
the pandemic in a hasty way without any meaningful consideration of new theorisations about

42

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

student learning. Almutairi et al, (2021) developed an emergency remote learning frameworkthat is mostly synchronous and utility-driven as a response to the learning and teaching crisis of
the pandemic era. This crisis was created by the pandemic and the results of Almutairi et al,(2021) show that multiple pedagogical approaches were used by IHEs human teachers to enable
students learning online. The use of traditional methods and practices of teaching such as
pedagogy in online learning is increasingly considered as obsolete. Studies on remote learning
beyond the pandemic such as those of Alenezi et al, (2022), Ndlovu et al, (2022) and Tzimiris etal, (2023) continue to theorise about remote learning within the emergency, crisis framework
dominated by synchronous learning conception and utility-mode use of technology in education.
In this article, I argue that post-pandemic era provides IHEs with opportunities to link anddevelop it beyond traditional methods and practices of teaching such as those maintained in postpandemic research on learning and teaching. Traditional meanings of teaching come for sharp
scrutiny in this article as relics of the past that needs jettisoning. The effort is intended to muster
new theorisations about learning and teaching within asynchronous and technology-as-essence
framework (Heidegger, 1954, 1977 Translation). Each traditional teaching mode consists of atarget (Skelton, 1995), that is, the learning participants and how they are treated in each learningand teaching encounter. This affects the degree of autonomy, self-determination, andindependence of students in the learning encounters (Blasche, 2012). The pedagogical models
that focus on instruction based on hard-coded knowledge, signify the role of a teacher as anexpert, thrive on passive students learning and strict class attendance remain entrenched in mostundergraduate studies (Soare, 2012). When remote learning was imposed, IHEs sought to retain
most of the features of pedagogy, such as, delivering content as close to in-person learning as
possible, making sure that students and teachers met online at the same time, students undertake
e-assessment as close as possible to in-person assessment techniques. These pedagogicalinterpretations of remote learning are retrogressive and infra dignitatem, below the dignity ofstudents in IHEs. Heidegger (1954, 1977 Translation) suggests that for technology to be allowed
to perform to its optimal level it would enable humans to progress to what Harari (2012) calls astate of homo deus, when humans become deities. There are concerns that such optimisation oftechnology would turn it into a harmful tool. The first concern relates to superintelligence whenadvanced technologies would possess an intelligence greater than the one possessed by a geniuslevel human being (Bostrom, 2014). This concern brings to sharp scrutiny unmitigated growthof technology beyond human comprehension and control. The concern, however, is impervious
to the role of IHEs in optimising human intelligence and smacks of scholasticism, narrow-mindedcommitment to tradition. Superintelligent technologies challenge humans to augment theirintelligence and abandon their debilitating traditions and religiosity. Telagogy provides anintellectual cleft to explore human intelligence beyond its current limitations. The basic missionof IHEs is to develop human intelligence and it cannot do so within their limiting traditions. IHEs
also need to revise their theoretical interpretation of formal learning as industrialisation ofteaching (performativity). Conceptualised as performativity, learning becomes enforcement ofindustrial rules and regulations, as well as replication of industrial processes with a strong techne’
episteme. Such learning still works within authority-subordinate relationships of pedagogy(Peters, 2006). This performativity learning reduces human intelligence to an industrial tool andcompromises the huge potential of human intelligence, a source of concern with43

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

superintelligence. Psychologised notions of learning from Piaget (cognitivist) and Skinner(behaviourist) represent IHEs’ traditions that ought to be challenged in this century.
This study combines the theoretical interpretations of learning, collectively referred to as
theories of independence, self-determination, and autonomy (Keegan, 2013), and include
Freire’s (1970) critical theory of learning, Invitational learning theory drawn from rhetorics(Pitso et al, 2014), and critical pragmatism (Tjabane, 2021). It contributes the concept of andjustifies advanced remote learning. Telagogy seeks to empower students to deal with concrete
community problems hence use of Empowerment Evaluation research method. It is aboutdeveloping social justice pioneers that make an impact in communities. Telagogy shifts
learning not only from synchronous and technology-as-utility framework but also from theunderlying epistemology of mimesis towards poiesis, that is, towards developing students’productive thinking, creativity, and innovation. Wertheimer (2020) argues that productive
thinking is about gaining insights on a particular concrete problem and using reasoned logic
plus evidence to craft a solution. AI systems such as chat-GPT would be beneficial for
productive thinking and would reconfigure learning away from in-person contact sessions andteacher-centred approaches. Telagogy describes new roles for teachers (Table 1, below).
Table 1
Theoretical Interpretations of Teaching: Locating Telagogy
Traditional

Performativity

Psychologised

Critical

Invitational

TargetElite children

Meritocracy

Individuals

Informed
Citizenry

Enterprising
Individuals

CriticalPragmatism
Pragmatic
activists

Location

Discipline

Rules &
Regulations

TeacherLearner
Relationship

Material
Conditions

Material
Conditions

Material
Conditions

Epistemic
Position

Puristresearchtraditions
Subject
expertStrongpragmatism

Subjective
interpretation

SocialchangeStrongpragmatism

SocialidealismStandards
enforcer

Psychodiagnostic

Criticalintellectualism

Enabler &co-participant

Pragmatic
activist

Purpose

CulturalReproduction

Systemefficiency

Effective
teaching

Emancipati
onFreedom &independence

Just &
equitable
society

MethodLectureWork-based
Learning

Teamwork

ParticipatoryInquirydriven

Collective
problemsolving

TeacherRole

44

Telagogy
Social justicepioneers
OnlineCommunities& Global
Well-being
Socialidealism
Digitalmaterial &onlinelearning
techniquesdeveloper,
automateddigitalassessment
developer,
advisory
Global citizen+ strong
ontologicalreality
Streaming,
curation,cloudcollaboration,
immersive
learning

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

Towards Telagogy: Concepts, Contexts, and Content
The first computer-assisted learning started off in the early 1960s and was called Programmed
Logic for Automatic Teaching Operations (PLATO). It represented the initial prototype oflearning in a virtual space followed by blended learning, online learning and now remotelearning. These computer-based conceptions of learning would undergo, in the next decade,possibly their highest development in the form of online streaming of educational courses along
the lines of Spotify or Netflix making new demands on higher learning. Firstly, students are
more likely to curate their own curriculum drawing educational courses from universities
across the globe and in real time as earlier stated. Secondly, students would study at their own
pace, place of preference, anytime as well as anywhere as they undertake e-assessment
whenever they are ready. This learning becomes self-directed, self-determined, active, highly
flexible, and removes stress in learning. It is positioned at quadrant 3 (Diagram 3, below) thatmeans incorporating all three levels of learning – individual, collective, and local levels.
Bowden and Marton (1998) redefined IHEs mission of teaching, research, and community
engagement as learning at an individual level (traditionally called teaching), learning at acollective level (research) and learning at a local level (community level). At an individuallevel, students learn knowledge that is unknown to them but well known by others, experts,
and communities of practice. In Diagram 3 below, students move from unknown to known,that is unknown to them as individuals but broadly known knowledge to known, known, thatis, students reach a stage of knowing knowledge that is already well known through mostly
mimetic, replication learning epistemology. Telagogy does not seek to eliminate individual
learning but suggests that this knowledge already exists in AI systems such as chat-GPT. The
suggestion is that the first year of study could be dedicated to providing an overview of
disciplinary knowledge so that from advanced undergraduate level, students can begin to tackle
concrete community problems. Community problems compel for disciplinary knowledge
grounding (individual learning), research skills (collective learning) and tackling community
problems (local level learning). Once students learn this way then they develop “quality ofwill”, the scale of commitment to resolving community problems and “knowledge ofconsequences”, degree of knowing one’s complicity and abdication of responsibility when thecommunity problems remain unresolved. It is argued in this article that community problems
are known but ignored and thus remain vague and unattended. In resolving these community
problems, students develop productive thinking skills and technological savvy necessary as
globe-trotting individuals. It is expected that telagogy, at some point, would pursue blue sky
research in quadrant 4.

45

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

Figure 1
Permutations of Telagogy

Telagogy is based on communities, both online and physical, thus its underlying essence is acommunity. This is based on the African concept of letsema/ilima. Letsema/ilima is a collective
assembling of community members driven by the spirit of ubuNtu (humanness, social justice)
to assist those less privileged in a community to stand up, rise and be able to do things forthemselves, that is, build a strong vukusenzele work ethic, rise and do it yourself. This explains
why telagogy needs an infusion of empowerment theory (Zimmermann, 2000). Empowerment
requires the following as described by the former Vice Chancellor of the South African
University of Cape Town and the co-founder of Black Consciousness Movement, Mamphela
Ramphele (2012):••

Substantial shift to global citizentry away from being treated as a subject. This meansthat one becomes a key agent of change in society who is inspired to tackle societal
challenges. In our African context, the journey to citizenry begins with a criticalawareness of woundedness from years of colonial ravages not only on land but also on
African collective dignity. Approaches to learning, in the African context and Global
South, have to take account of the deep-seated inequality and poverty hence the needfor the lestsema/ilima circle model that leverages firstly, the critical awareness ofexisting resources, knowledges and insights within a community that unleash citizens
fortitude to tackle their own problems. Secondly, generate ideas through ideational
bricolage that can be converted to real solutions of pressing community problems.
Ideational bricolage is the explicit identification of idle resources within a communitythat could help find solutions to pressing problems. Thirdly, apply solutions to address
identified community problems. Once the circle is completed then it can be iterated.
Develop a strong sense of autonomy, capabilities to do things on their own to gain
vukusenzele work ethic. This is similar to Zimmermann’s (2000) theory of
empowerment. Empowerment theory refers to a situation where communities or

46

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

individuals overcome their psychological oppression, become increasingly aware ofcommunity problems and combine their capabilities to resolve these problems driven
by a strong letsema/ilima motif and the notion of vukusenzele work ethic. This
meaning of empowerment goes beyond the traditional psychological conception of
empowerment as increased self-esteem, self-efficacy, self-actualisation competences
and locus of control (Perkins, 1995, Zimmerman, 2000, Silverton, 2018).
Another area of telagogy worth our attention is the use of chat-GPT in influencing various
aspects of students’ learning. Studies have focused on student and teacher perceptions of chatGPT use, possible plagiarism and how it affects students’ motivation (Munoz et al, 2023). It isalso seen as critical in shifting students’ learning towards innovation and creative problem
solving. Advanced technologies have “ushered in a new era of innovation and creativity inseveral disciplines, including education” (Munoz, et al, 2023: 3). Studies show that when chatGPT is prompted for answers for assignment completion, it provided accurate responses to theprompted assignment question (Patel, 2023; Halaweh, 2023). Some universities are alreadydeveloping guidelines for use of chat-GPT in assignments. In this study, the relationships
between chat-GPT and student assignments was probed in terms of time of assignment
completion and how it assisted students to solve concrete problems. Figure 2 below describes
these relationships. In the first instance, students test chat-GPT for the assignments given tothem in their respective courses and as they do so, students measure the average time it takes
them to complete each item of the assignment and compare it with the average time of doing
the assignment manually. In the second instance, students prompt chat-GPT to assist them toframe a concrete problem in ways that helps them develop possible solutions. This includes
prompting for innovative solutions.
The starting point of the conceptual framework designed to investigate chat-GPT is an ecollaborative workspace assembled in similar fashion as letsema/ilima and applying the
vukusenzele work ethic. Letsena/Ilima e-collaborative workspaces are voluntary and selfdetermined, empowering community practices (Lebeloane and Baffour, 2008). In theseassemblages, students meet to resolve a theoretical or practical problem in a collaborativeenvironment employing the work ethic of vukuzenzele meaning arise and do it yourself in lieu
of being dependent on another person or conditioned to believe that another person has to be
in charge in order for a problem to be solved. In the context of students’ learning, it marks amajor shift towards students’ agentic power in the act of learning. Learning, under these
conditions, proceeds on the basis of either a theoretical or real problem. It involves further
prompts for chat-GPT on possible innovative solutions. Telagogy would be based mainly on
e-collaborative spaces that challenge real problems and less on theoretical problems. It has
strong shared ideas and shared solutions approaches to real problem solving. The next section
describes in detail a study using chat-GPT.

47

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

Figure 2
Diagram of Telagogy

Methodology and Methods
The study is based on Empowerment Evaluation (EE) research method. It is an approach toresearch that helps participants to not only identify variables or gaps in literature thatcompromise ongoing project’s performance but also provides possible solutions to these
problems (Zimmermann, 2000; Fetterman, 1994; Fetterman, 2019). It makes use of qualitative,
quantitative, and even mixed methods approaches. The participants were drawn from a pool ofadvanced undergraduates from Chemical Engineering (N=5), Logistics (N=5), and Accounting(N=5) through use of a purposive sampling. Patton (2002) defines it as selection of data-richcases for effective use of limited resources. Teachers of second and third-year students wereapproached in each respective discipline to recommend students that could participate in the
study. It was emphasised that, in line with the ethical clearance, students would participate
voluntarily in the study and could leave anytime without any repercussions.
A qualitative EE method called Participatory Evaluation Design was used in this study which
consisted of the following phases: training, illumination, facilitation, advocacy, and liberation(Fetterman, 1994). Step 1 of the research design involves responsible planning which entails
involving research participants in planning the research. In this phase, students elaborate on
their understanding of chat-GPT, its use, and practical applications in their learning. For those
who had not been exposed to chat-GPT (about 30% of participants), basic training on use ofchat-GPT was conducted. It was downloaded on the laptops, provided to them during the
COVID-19 pandemic. Participants trained one another on the use of chat-GPT in their various
assignments. This training session was intended to forge collaboration and identify groupdynamics in team formation as per the framework developed by Pitso (2020) - pre-connectivity
connectivity, early superficial learning, intense interactivity, maturing, deep learning, andresolution. These team formation stages were also intended to serve as an analytical tool forinterpretation of collected data. The researcher intended to become a keen observer whointerviewed participants in each stage of team formation. Observation included carefully noting
participants’ interactions, particularly points of agreement, differences, and emerging themes

48

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

of cooperation, democratisation of the collaboration space, inclusivity, openness, and degreeof flexibility and reflexivity. Interview questions covered issues relating to participants’solicitation of community views on the problem they sought to resolve, their experiences fromthis research and overall participation in the collaboration. Step 2 and step 3, involved findingout whether participants show a strong sense of owning the process, inclusivity, flexibility, andopenness to use and discuss issues relating to chat-GPT. Written semi-structured interviews
were conducted. Thereafter, participants were allowed to identify and select concrete problems
drawn from their own experiences and had to agree to tackle only one problem for the purposeof this research study. The problem had to emanate from a local community as one of therequirements of the study was for participants to solicit views of select community members.
Once such a consensus on a concrete problem was reached, participants prompted chat-GPT togain better understanding of the problem. Participants also visited a local non-profit
organisation to find out its views on the problem at hand. These interviews at the local nonprofit organisation were conducted once but ideally, it is suggested that more follow-up
interviews are necessary. These stages of research are called illumination and facilitation
respectively.
In step 4, students develop a solution prototype and showcase it (advocacy). In the last step,
students find a sense of satisfaction for resolving or creating conditions for the resolution of asocial problem, “quality of will” and the consequences of their actions are positive (liberation).
Written interview schedules were administered to students during the study and post-study.
Post-study interviews were intended to check lessons learned and whether participants wereready to embrace learning based on productive thinking, empowerment theory and AI systems.
Issues of validation of research are equally relevant in EE research methods and take the formof qualitative trustworthiness despite Fetterman’s (1995) argument that they are less importantin empowerment discourses. Truth-value and acknowledging inherent biases in qualitative
research designs and sampling techniques are essential in legitimising qualitative research(Noble & Smith, 2015). Truth-value refers to verifiability or falsity of a claim and triangulationor corroboration serves to make a determination of the veracity or mendacity of a claim. Useof two sources of data – observation and interviews – was considered adequate to corroborate
for verifiability. Accounting for possible biases was also done carefully, in addition toauditability meaning providing clearer and transparent description of the research process(Noble & Smith, 2015). Finally, there was a need to describe the context of the study and offer
thick as well as rich verbatim descriptions of participants’ views in support of findings.

49

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

Figure 3
EE Participatory Evaluation Design

Results
Data collected in a qualitative study of 15 students that participated in testing the efficacy ofchat-GPT in students’ assignments and its use in solving a concrete problem were analysed todetermine:••

The relationship between students’ duration of completing an assignment using chatGPT as compared to manual completion of an assignment plus potential for plagiarism.
The relationship between students’ use of chat-GPT in attempting to solve a concrete
problem and the time of finding solutions was qualitatively tested through interviews
with participants. The interviews also included perspectives on whether concrete
problem solving helped them become innovativeness.

The variables such as age, socio-economic status of students, level of experience in using AI
systems and students’ nominal-scale variables such as gender, ethnicity and race were notconsidered for any meaningful analysis. This was essentially a qualitative, exploratory study.
It was intended to demonstrate how AI systems and empowerment theory infused into learningand teaching could enhance better understanding of AI systems and their applications in IHEs
within the framework of technology-as-essence. This framing of technology could allow
remote learning to develop to its next level of online streaming and thus provide opportunities
to theorise about learning and teaching beyond its current limitations.
The interview data shows that 70% of the participants, although it was not a consideration
when recruiting, were already using chat-GPT for assignments and were aware of theplagiarism consequences so avoided copying answers from chat-GPT. Most participants
indicate that they have had to include in their answers to assignments, information from othersources and curate such knowledge to fit assignment demands. “you gotta realise and becomeaware of penalties linked to copied text so adjust your answers accordingly” commented oneof the participants. In the use of chat-GPT, participants showed a good understanding ofplagiarism rules and made effort not to copy answers given to them by chat-GPT. These
interviews also show that chat-GPT substantially reduces the time to complete assignments
based on existing knowledge and is also capable of suggesting innovative ideas when the50

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

problem is sufficiently specific. When asked whether participants found chat-GPT helpful, one
participant commented “chat-GPT saves time and allows one to focus on other things. ”
The students found the first stage of the EE method quite useful in familiarising themselveswith chat-GPT particularly those who were using it for the first time. While chat-GPT did not
substantially reduce the time for completing projects based on a concrete problem, it was usefulin clarifying the problem at hand which assisted students’ discussions on framing of the
problem.
In another study, chat-GPT proved to be better than students at creative problem-solving (Webbet al, 2023). In this study emphasis was on productive, creative problem-solving. The meaningof a problem offered by engineering students as a gap between a current situation and adesirable one was quite useful to students’ analysis of a concrete problem. A number of factors
were identified that caused a current situation to be less than desirable and the ideal situation
was described prior to seeking solutions even before prompting chat-GPT. My further
observation of participants in attempting to do their project was analysed in terms of Pitso’s
revised group dynamics process as used for human-machine collaborations (Pitso, 2020). The
Smart Team Formation Process (Pitso, 2020) includes:
1. Pre-Connectivity
This stage involves students familiarising themselves with an AI system underinvestigation (chat-GPT) and its role in assignments or problem-solving. It also
indicates, in early formations of the collaborative team, some anxieties, scepticism,doubt and cynicism from participants concerned with whether a multi-disciplinary team
could work together given its diverse knowledge bases and experiences. My
observation of this team was that the use of chat-GPT for purposes of familiarisation,
stage one of the method, tends to bring the participants closer when they all participate
in using chat-GPT to find answers for assignments of one group. For instance, when allof them become involved in seeing how Chat-GPT answers those specific engineering
assignments it helps bridge epistemic distances between students and enhances theirco-operative spirit in the collaboration spaces. “I never thought I could be involved in
an assignment from other courses, this was interesting”, a comment from a participant.
When introduced to a real, concrete problem, students have already begun to create
some understandings of how their discussions should proceed. I observed a greater
understanding in using chat-GPT and the increased confidence in the answers promptedfrom chat-GPT and the realisation that chat-GPT contains terabytes of great content
that helps them better understand the problem at hand (Stirling, 2020).
2. Connecting/Connectivity
An increasing interest in the use of chat-GPT to solve a concrete problem helped toreduce apprehension and doubt in the interactions between participants and chat-GPT.
Pitso’s (2020) study on group dynamics suggests that teams function better and interact
with AI systems confidently when there is a clear and lucid project that students

51

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

undertake. It is in this stage that students discussed various community problems that
could be their project. Participants settled on potholes that have become a major
problem in the South African context compromising logistics and general well-beingof communities. When prompting chat-GPT on the meaning of a pothole, the following
responses were given by chat-GPT: [A type of a road surface damage that usuallyappears as a depression or hole. It is usually caused by wear and tear, weather
conditions, or the deterioration of road surface. Potholes can vary in size and shaperanging from small, shallow depressions to larger, deeper holes. Potholes form whenmoisture seeps into the road’s surface weakening the underlying layers]. While roadmaintenance and repair falls under the local government purview, most of them are
dysfunctional leading to persistent potholes problems. The most important issue about
the project is that none of the participants are trained on the particular problem at handand have to test the limits of their knowledge and experience. “I found the explanationsof a pothole quite useful and easy to find in chat-GPT”, one of the participantscommented. There was also an increasing confidence that the problem at hand could be
solved given the role of chat-GPT in providing ready-made answers.
3. Early Superficial Learning
Participants further probed chat-GPT on possible solutions with the following
responses: [patching for smaller holes, it involves filling the hole with materials suchas asphalt. Potholes filling machine...to fill potholes with hot asphalt. Cold mix asphalt,
ready to use mixture. Resurfacing or overlaying, add new layer of asphalt on existing
pavement. Proper road maintenance. Advanced road construction techniques such as
durable materials, better drainage systems, and proper designs.]. While thesesuggestions were important, most of them were at a level of municipalities that requiredhuge resources. Participants felt constrained by these chat-GPT responses. This was a
crucial moment where participants were exposed to which also showed the limits not
only of chat-GPT but also of reproductive knowledge. The greater realisation of thesuperficiality of such information and inadequacies in helping participants to solve apressing problem meant that participants had to go beyond current solutions of potholefilling.
4. Intense Interactivity
Participants were increasingly becoming aware that chat-GPT had its own limitations
in responding to some of the questions: “Obviously chat-GPT is unable to give us all
answers”, commented a participant. Yet, this was a crucial moment when students
ought to interact more intensely with chat-GPT to find possible solutions. My
observations confirm, the problem with participants at this stage, was that they haverarely been involved in activities that transcend their reproductive thinking box. Intenseinteraction with chat-GPT was restricted not by capabilities of chat-GPT but by
participants’ mastery of known knowledge which now proceeded to the use of chat-52

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

GPT within the same reproductive vein. There was a need for epistemic border crossing
not at a level of disciplines but at the level of participants’ mindset.
5. Maturing
There was, however, greater focus on the project at this stage and participants were able
to overcome personal concerns, anxieties, and cynicism. The interview questions
focused on how participants felt at this stage of the study. “We are frustrated because
chat-GPT answers are for the municipality and we are expected to try out our own
solutions”. It is important to note that the response relates to a project and no longer onparticipation and initial use of chat-GPT. This was an important development towards
participants’ sense of growth and learning.
6. Deep Learning
The frustration with chat-GPT presumed inadequacies which, in essence, emanatedfrom participants’ reliance on hard-coded knowledge, although there was a need to
explore possible solutions outside this knowledge. Deep learning works on
unsupervised forms of learning which is commonly called machine learning capability
where AI systems are employed to help resolve real world problems known for theircomplexity, uncertainty and unpredictability. This was an overwhelming experience forparticipants and I have had to, as an active netnographic lurker, suggest that participants
prompt chat-GPT for innovative solutions to potholes filling and one of the responses
included self-healing potholes. This idea fascinated participants who wanted to know
more about it. The participants then prompted chat-GPT on self-healing potholes.
[These innovative technologies allow potholes to repair themselves without the needfor human intervention. Researchers are working on engineering asphalt mixes thathave the ability to self-heal. Some studies explore the use of bacteria that produce
calcium carbonate]. Participants, in their discussions had a strong propensity to research
this area of potholes further and involve Chemistry students. This is how far the study
could go with a huge potential for participants to be at the forefront of crafting
innovative solutions.
Resolution
This is the stage where participants develop prototypes on the unique idea they haveestablished. In the case of the study, participants would have joined the exploration ofself-healing potholes but brainstormed alternative asphalt mixes that do not include theones suggested by chat-GPT. They could also have calculated the costs of the idea andmade their findings public through showcasing. However, participants were unable toreach this stage because of time constraints.

53

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

Discussion
The purpose of this study was to develop better understanding of remote learning as a “newnormal” in learning and teaching post-pandemic as well as explore possibilities of its advanced
form. The data collected in this study is of a qualitative nature making for lack of generality
and precision. However, conclusions of this study are relevant and important to IHEs struggling
to progress to the next level of remote learning and consider in-person contact sessions as relicsof the past. The synchronous remote learning conceptualised within technology-as-utility
framework is not sustainable given the impact of AI systems on learning and teaching that
increasingly shifts learning control to students. In this study, there was strong indication of
students taking active control of their learning through deciding their own project, moments ofprompting chat-GPT, discussions, suggestions and probing possible solutions. Post-study
interviews with participants show gain in greater control of their own learning. This is the mostimportant and emerging advantage of remote learning. I argue that remote learning would leadto even greater student control when it is conceptualised as asynchronous and AI systems
development occurs within technology-as-essence framework. This would enable students todecide when to access educational courses and projects, including from any university, decideon when to take examinations and from anywhere. When questioned post-study on the meaning of
this possibility, participants were a bit skeptical. This shows that it takes more time to shift fromtradition to new spaces of development. My observations of confident students tackling a real
problem and post-study interviews showed a glaring gap between attempts of research andreality as well as the power of institutional cultures. There is a glaring gap in research on AI
systems that needs further investigation. For example, the slow embracing of AI systems byparticipants particularly in terms of infusing them into their practices and the benefits accruedby students when using AI systems.
Participants also showed a positive progression through different stages of team formation
process. My observation shows that participants, with minor variations, were able todemonstrate features of each stage of this process. Chat-GPT showed potential in finding
innovative solutions to a real problem. Students were also able to sidestep plagiarism by not
only rewriting chat-GPT prompts but also included additional information from the textbooks.
Conclusion
The traditional focus of undergraduate studies on mastery of universal hard-coded knowledge
mostly bereft of cognitive content of communities of origin or of interest to students require
serious attention (McGhie, 2012) given that hard-coded knowledge is already available in AI
systems such as chat-GPT. There is no point in trying to take students through this hard-codedknowledge over the stretch of three years when the use of chat-GPT in the first year ofundergraduates studies could cover it within a year. Advanced undergraduate studies could
then focus on the development of productive thinking through focus on concrete community
problems with a strong understanding that learning is socially situated and constructed (Akpan
et al, 2020). Productive thinking thrives on a Gestalt, holistic approach that concrete
community problems offer. Other studies on socially situated and constructed learning

54

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

accentuate learning that is a social and cultural process occurring in the context of humanrelationships and activities. This view assumes that a socio-cultural context should be the basisof student participation in the affairs of their communities, first summon knowledge fromwithin these communities and supplement it with formal hard-coded knowledge (Lave andWenger, 1991; Akpan et al, 2020). The traditional undergraduate studies that focused on “inthe-head” learning that tended to reduce human mental potential to information-processing
machine and a storage device with a strong memory strength that contained highly developed
retrieval mechanisms has come under intense pressure in this era. AI systems have rendered
this approach to learning unnecessary as such knowledge can now be easily accessed via AI
systems. The undergraduates’ mind can be put to better use which, actually, could play apositive role in their communities. New learning that is suggested in this article referred to as
telagogy draws significantly from learning that emphasises students’ collaborative effort thatleverages their interactions, knowledge sharing, collective research, critical discussions anduse of AI systems in attempts to resolve concrete community problems. Telagogy is therefore,
an online streaming of educational courses sourced from various universities across the globe
and available for access anytime and from anywhere. It makes use of advanced AI systems
such as chat-GPT to curate and prepare knowledge for creative complex responsive processes
that include localised insights and resources for creative, complex responsive processes. It
needs further research and development.
Recommendations
The investigation undertaken in this article was twofold. It sought to better understand students
learning from the asynchronous and technology-as-essence framework. The investigation
sought to transcend remote learning research that tended to lock its debates on emergency/crisis
remote learning implementation during the pandemic. It is suggested that further research isnecessary to qualitatively and quantitatively investigate the efficacy of this framing of students’
online learning as asynchronous and open to being shaped by continual advances in technology.
There is also a need for IHEs to develop guidelines for use of AI systems such as chat-GPT on
enhancing students learning. Advanced remote learning offers opportunities for IHEs to shift
undergraduate studies away from mimetic epistemologies of replication to poiesis with a strong
motif of creativity, innovation and complex problem solving. This also shift students’ learningfrom developing reproductive thinking towards productive thinking. The suggestion is that
reproductive thinking can be developed in the first-year of students learning and advanced
undergraduates ought to increasingly focus on productive thinking. EE research methods alsoneed to be refined to fit into researching learning and teaching.

55

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

References
Akpan, V., Iqwe,U., Mpamah, I., & Okoro, C. (2020). Social constructivism: Implications onteaching and learning. British Journal of Education.
Almatutairi, F., & Ghuloum, H. (2021). A novel framework for facilitating emergency
remote learning during the Covid-19 pandemic. International Education Studies
14(5), 121–134. https://doi.org/10.5539/ies.v14n5p121
Appiah, K. (2005). The Ethics of Identity. Princeton. Princeton University Press.
Alavi, S., Abuja, V., & Medury, Y. (2010). Building participation, reciprocity & trust:
Netnography of online community of APPLE using regression analysis for prediction.
Apeeje Business Review, 11, 82–96.
Asa Ryegard, K., & Olsson, T. (2010). A Swedish Perspectives on Pedagogical Competence.
Copenhagen, Denmark: Dansk University.
Banholzer, V. (2022). From industry 4.0 to society 5.0 & industry 5.0: Value and missionoriented policies. IKOM Working Paper.
Bengry-Howell, A., Wiles, R., Nind, W., & Crow, G. (2011). A Review of the Academic
Impact of Three Methodological Innovations: Netnography, Child-led Research andCreative Research Methods. Accessed from https://www.ncrm.ac.uk/
Bernstein, B. (1990). Class, Code & Control. Vol. 4 The Structuring of Pedagogic Discourse.
Abington: Routledge.
Boshier, R., & Huang, Y. (2008). In the house of the scholarship of teaching and learning(SoTL), teaching lives upstairs and learning in the basement. Teaching in Higher
Education, 13(6), 645–656. https://doi.org/10.1080/13562510802452368
Bowden, J., & Marton, F. (1998). The university of learning: Beyond quality andcompetence. Education + Training, 41(5). https://doi.org/10.1108/et.1999.41.5.ii.2
Anderson, T. (2016). Getting the most from the learning management system Accessed
01/03/2022 from https://teachonline.cg
Boyer, E. (1990). Scholarship reconsidered: Priorities of the professoriate. New York: The
Carnegie Foundation for the Advancement of Teaching.
Ball, S. (2012). Performativity, commodification & commitment. An I-spy guide to the neoliberal university. British Journal of Education Studies, 60(1), 17–28.
https://doi.org/10.1080/00071005.2011.650940
Bayne, S., Evans, P., Ewins, R., Knox, J., Lamb, J., Macleod, H., O’Shea, C., Ross, J., Sheail,P., & Sinclair C. (2020). The Manifest for Teaching Online. Cambridge: MIT Press.
https://doi.org/10.7551/mitpress/11840.001.0001
Beauvoir, S. de (1947). The Ethics of Ambiguity. New York: Philosophical Library, Citadel.
Blasche, L. (2012). Heutagogy and lifelong learning: A review of heutagogic practice andself-determined learning. International Review of Research in Open and Distance
Learning, 13(1), 57–70. https://doi.org/10.19173/irrodl.v13i1.1076
Brown, A. (1995). Advances in learning and instruction. Education Researcher, 23(4): 4–12.
https://doi.org/10.3102/0013189X023008004
Butler, D. (2020). Designing Sustainable Digital Transformation of Learning. Accessed
01/03/2022 from https://www.beyond-events.eu

56

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

Buxton, E. (2014). Pharmacists’ perception of synchronous versus asynchronous distancelearning for continuing education. American Journal of Pharmaceutical Education
78(1), 1–9. https://doi.org/10.5688/ajpe7818
Creswell, J,. & Plano Clark, W. (2011). Designing and Conducting Mixed Method Research
2nd Eds. Thousand Oaks: SAGE.
Costello, L., McDermott, M., & Wallace, R. (2017). Netnography: Range of practices,misperceptions and missed opportunities. International Journal of Qualitative
Methods, 16, 1–12. https://doi.org/10.1177/1609406917700647
Elliot, G. (2012). Policy, performativity & partnership: An ethical leadership perspective.
Research in Post-Compulsory Education, 17(4), 423–433.
https://doi.org/10.1080/13596748.2012.738977
Gardner, H. (1991). The Unschooled Mind. New York: Basic Books.
Hayes, D. (2017). Beyond McDonaldization of Higher Education. Abingdon, UK: Routledge.
https://doi.org/10.4324/9781315270654
Fetterman, D. (1994). “Empowerment Evaluation”. Evaluation Practice, 15(1), 1.15.
https://doi.org/10.1177/109821409401500101
Fetterman, D. (2019). Empowerment evaluation: A stakeholder involvement approach. Wiley
Australian Health Promotion, 30(2), 137–142. https://doi.org/10.1002/hpja.243
Halaweh, M. (2023). Chat-GPT in education. Strategies for responsible implementation.
Contemporary Educational Technology, 15(2), 1-11.
https://doi.org/10.30935/cedtech/13036
Halupa, C. (2015). Pedagogy, Andragogy & Heutagogy. Accessed 01/03/2022 fromwww.researchgate.net.
Heidegger, M. (1954, English translation, 1977). The Question Concerning Technology. New
York: Garland Publishing.
Heidegger, M. (1935, Translation, 1959). Introduction to Metaphysics. Yale: Yale university
Press.
Junco, R., Heibegger, G., & Lokan, G. (2010). The effects of Twitter on college students
engagement and grades. Journal of Computer Assisted Learning, 27(2), 119-132.
https://doi.org/10.1111/j.1365-2729.2010.00387.x
Koester, A. (1967). Ghosts in the Machine. UK: one 70 Books.
Kohlberg, L. (1981). Essays on Moral Development, Vol. 1: The Philosophy of Moral
Development. San Francisco: Harper & Row.
Lave, J., & Wenger, E. (1991). Situated Learning: Legitimate Peripheral Participation.
Cambridge: Cambridge University Press.
https://doi.org/10.1017/CBO9780511815355
Liew, W. Effects beyond effectiveness: Teaching as a performative act. Curriculum Inquiry
43(2), 261–288.
Lebeloane, L., & Baffour, K. (2008). Letsema: A way of inculcating African and preserving
African indigenous knowledge in the youth through formal education in the 21st
century. Journal of Educational Studies, 7(2), 43–49.

57

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

Lynch, K. (2010). Carelessness: A hidden doxa of higher education. Arts & Humanities inHigher Education, 9(1), 54–67. https://doi.org/10.1177/1474022209350104
McGhie, V. (2012). Factors Impacting on First-Year Students’ Academic Progress in a South
African University. Stellenbosch: Doctoral Thesis.
Marton, F., Alba, D., Elizabeth, G. (1993). Conceptions of learning. International Journal of
Educational Research, 19(3), 277–300.
Munoz, S., Gayoso, G., Huambo, A., Tapia, R., & Incaluque, J. (2023). Examining theimpacts of Chat-GPT on students’ motivation and engagement. Social Space, 23(1),1–28.
Neuwirth, L., Svetlana, J., & Mukherji, B. (2021). Reimagining higher education during andpost-Covid-19: Challenges & opportunities. Journal of Adult & Continuing
Education, 27(2), 141–156. https://doi.org/10.1177/1477971420947738
Noble, H., & Smith, J. (2015). Issues of validity and reliability in qualitative research.
Evidence-Based Nursing, 18(2), 34–35. https://doi.org/10.1136/eb-2015-102054
Nussbaum, M. (1996). For the Love of Country. Boston, MA: Beacon Press.
National Forum: For the Enhancement of Teaching and Learning in higher Education (2020).
Accessed 01/03/2022 from www.teachingandlearning.ie
Nussbaum, M. (1996). For the Love of Country. Boston, MA: Beacon Press.
Perkins, D. (1995). Empowerment, theory, research and application. American Journal ofCommunity Psychology, 23(5), 569–579. https://doi.org/10.1007/BF02506982
Pitso, T., Lebusa, M., & Kok, L. (2014). Accounting for undergraduates’ teaching
perspectives in a scholarly teaching encounter. South African Journal of Higher
Education, 28(4). https://doi.org/10.20853/28-4-397
Pitso, T. (2018). Shared futures: Exploring the collaborative potential of intelligent
technologies and human ingenuity in cocreating value. In Sílvio Manuel Brito (Ed.)
Toward Super-Creativity. https://doi.org/10.5772/intechopen.85054
Pitso, T. (2021). Contextualised critical reflections on academic development practices:
towards professional learning. Stellenbosch, South Africa: African Sun Media.
Pitso, T. (2023). The Forgotten: Reconstructing and Reclaiming African Spirituality in the
Post-truth Era. Stellenbosch, South Africa: African Sun Media.
https://doi.org/10.2307/j.ctv1nzfwkj
Power, M. (2014). Do scholars need performance free time & space? Times Higher
Education. Accessed 01/03/2022 from http://www.timeshighereducation.co.uk.
Mamphela, R. (2012). Unleashing the power of communities to confront health inequities. A
Accessed 01/07/2022 from letsemletsemacircl.com
Reynolds, K. (2015). Performativity in higher education: An autoethnographic commentary& call to servant leadership. Proceedings of Teaching & Learning Conference held at
London School of Business & Management. Accessed fromhttps://www.academia.edu/35893093/Performativity_in_Higher_Education_An_Auto
ethnographic_Commentary_and_Call_to_Servant_Leadership_in_UKHE
Silverton, C. (2018). From reflexivity to collaboration: Changing roles of a Romani scholar,
activist and performer. Critical Romani Studies, 1(2), 76–97.

58

IAFOR Journal of Education: Technology in Education

Volume 11 – Issue 2 – 2023

Skelton, A. (2005). Understanding Teaching Excellence in Higher Education. London:
Routledge.
Tjabane, M. (2021). Evaluating concepts of teaching excellence in higher education. In T.
Pitso (Ed.), Contextualised Critical Reflections on Academic Development Practices:
towards Professional Learning. Stellenbosch, South Africa: African Sun Media
Publications. https://doi.org/10.2307/j.ctv1nzfwkj.7
Torres, R., & Cruz, O.-D. (2022). Remote learning: Challenges & opportunities for educators& students under the new normal. Anatolian Journal of Education, 7(1), 83–92.
https://doi.org/10.29333/aje.2022.717a
Vosniadou, S. (1996). Towards a revised cognitive psychology for new advances in learningand instruction. Learning and Instruction, 6(2), 95–109.
https://doi.org/10.1016/0959-4752(96)00008-4
Warren, J. (2023). Chat-GPT Reveals Uncomfortable Truth about Undergraduate Skills.
Accessed 03/08/2023 from www.timeshighereducation.co.uk
Watkins, C., Carnell, E., & Lodge, C. (2007). Effective Learning in Classrooms. London:
Paul Chapman Publishing.
Watts, L. (2016). Synchronous and asynchronous communication in distance learning. A
review of the literature. Quarterly Review of Distance education, 17(1), 23–32.
Webb, T., Holyoak, K., & Lu, H. (2023). Emergent analogical reasoning in large language
models. Nat Hum Behav (2023). https://doi.org/10.1038/s41562-023-01659-w
Wright, I. (2020). In Peak of Higher Education – A New World for the University of the
Future Report. Accessed on 14 /07/2022 from available@ey.com
Zimmerman, M.A. (2000). Empowerment Theory. In: Rappaport, J., Seidman, E. (Eds.)
Handbook of Community Psychology. Springer, Boston, MA.
https://doi.org/10.1007/978-1-4615-4193-6_2
Corresponding author: Teboho Pitso
Email: biki@vut.ac.za

59