










































 

EDUCATIO : Journal Of Education 
Volume 9 , Number 2, November 2025 

 ISSN : 2579-8383 (Print) ISSN : 2579-8405 (Online)  

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GenAI Fuzziness Towards Constructivist Pillars in Higher 

Education Institutions in Tanzania 

 
Shima Dawson Banele 

College of Business Education, Education Department 

shimadawson@gmail.com, shima.banele@cbe.ac.tz  

 

Accepted: 

10 August 2025 

reviewed:  

5 September, 2025 

Published:  

20 November 2025 

 

Abstract: The paper evaluated the constructivist pillars’ standpoint in the GenAI integration in 

the classroom settings among students in the selected Higher Education Institutions (HEIs).  

Objectives covered were to examine the module instructors’ feelings and determine the students’ 

views on constructivist gaps resulting from the utilization of GenAI. The mixed approaches were 

followed and engaged 5 randomly, and the sample size of 150 respondents was selected from 

Higher Learning Institutions (HEIs) in Dar es Salaam City, Tanzania. Data were collected through 

semi-structured interviews and a four-point Likert scale questionnaire, analysed using thematic 

content and Microsoft Excel. Findings were presented using quotations of the themes, tables, and 

figures. Findings disclosed that the GenAI deployments disrupted the teaching and learning 

triangle; instructors required enough time to authentically guide the students on proper usage of 

GenAI for building constructivist pillars. Findings showed that learners were highly dependent on 

GenAI for learning (90%) being implying the impacts on constructivist capabilities that need to 

be accommodated in the learning process. Also, it was found that ChatGPT is the popular GenAI 

among the students. Still was found knowledge, competencies, contextual comprehension, and 

social attributes continued to perform well in the constructivist pillars. The practice 

recommendations are made to HEIs and module instructors to guide the students in balancing the 

use of GenAI to support the acquisition of constructivist pillars for the attainment of curriculum 

goals. 

 

Keyword:  Constructivism, GenAI, HEIs, Students, Instructors 

 

Introduction 

Artificial Intelligence (AI) has been introduced for use in various aspects since 2022 

(Noroozi et al., 2024).  According to Sengar et al. (2024), AI comprises an innovative dataset that 

works as Generative Artificial Intelligence (GenAI). Scholars from different education contexts, 

levels, and perspectives recommended the use of GenAI in two folds: first, as a tool for improving 

pedagogical practices through assisting language learning, provision of personalized learning and 

feedback, and supporting the undertaking of the qualitative and quantitative research (Hsiao & 

Tang, 2024; Chan, Lo & Wong, 2024). Nevertheless, Nutsugah & Senanu (2024) revealed that the 

second fold of GenAI is vested in its capacity for supporting the acquisition of the intended 

educational learning outcomes. Moreover, in teaching and learning, there are disadvantages 

associated with overutilization of GenAI in pedagogical practices, as it leads to fragmentation of 

learning paths, hindering creativity and innovations, thereby disordered the constructivism and 

mailto:shimadawson@gmail.com
mailto:shima.banele@cbe.ac.tz


  
 

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cognitivism pillars (Noroozi et al., 2024). Additionally, ChatGPT is renowned and famous, 

accepted GenAI utilized by learners, facilitators, instructors, and researchers because it is built with 

capabilities to generate digitally-based content in the form of images, audio, texts, and videos 

(Hsiao & Tang, 2024).  

Constructivism as a learning theory is rooted in cognitive psychology (Acharya, 2024; 

Renninger, 2024). According to Piaget (1969), the constructivist pillars are built on learners’ 

cognitive capability to construct knowledge. Constructivists are further characterized as being 

dynamic in knowledge construction, receiving, and handling (Sepriyanti & Kustati, 2024). Also, 

constructivists’ attributes pinpointed that learners are pedagogical inputs, who are supposed to 

engage in designing, assessing, and developing the learning processes, approaches, and outputs (Al 

Abri et al., 2024). The involvement and engagement of learners in every stage of teaching and 

learning are to ensure activeness, become goal-oriented, and provide tangible feedback for 

improvements of the processes. Likewise, learners as the object of the teaching and learning 

processes are relatively responsible for rebuilding prior knowledge and experiences to build the 

foundation for the acquisition of new learnt content.  

Undoubtedly, under constructivist theory, the instructors’ roles in the teaching and learning 

process are to catalyse and capacitate the learners into actionable strategies and approaches 

fostered by linking, organizing, assimilating, and transferring the newly learned contents into 

optimized ways (Wibowo et al., 2025). The origination and dedication of constructivist processes 

are built on the mental schemas that are engaged in receiving, processing, and temporarily storing 

the content for use in the working short-term memory; thereafter, transferred, accommodated, 

stored, and retrieved to and from the long-term memory (Happs, 1985). According to Renninger 

(2024) and Banele (2023), cognitivism has to be built on Cognitive Load Theory (CLT) and 

Cognitive Load Optimization (CLO).  Cognition optimization is reached when the learners’ mental 

structures are struggling to build the blocks for accommodating the new knowledge based on the 

nodes of the existing ones, hence simulating the active learning processes (Al Abri et al., 2025; 

Wibowo et al., 2025). The activation of the knowledge relative to the existing situation 

differentiated the pieces of information being stored and processed for retravelling from the 

mental structure for future utilization (Sepriyanti & Kustati, 2024).  

The learning materials, skills, knowledge, and competencies acquisition; procedures for 

preparing, administering, and issuing assessments, evaluations, and research are highly impacted 

by the GenAI practices (Kolade, Owoseni & Egbetokun, 2024). Subsequently, the education-

delivering processes are formally and informally digitalized, indicating lifelong learning, whereas 

contents are quickly accessible at hand anytime and anywhere through AI innovations (Masrek et 

al., 2024). On the positive side, GenAI, as machine learning and crowdsourcing, possessed 

interactive tutors and virtual assistive deployments (Joshi et al., 2024) and offered appropriate 

learning lightning support at any time, place, and pace (Folman, 2025). Based on Kolade et al. 

(2024), the utilization of GenAI as cloud spaces enabled instructors to prepare hands-on 

algorithmic content for different disciplines, including mathematics, statistics, sciences, languages, 

and others, within a short time frame. Similarly, Lagos-Castillo et al. (2025) insisted on GenAI 

capacitating the instructors to quickly prepare assignments, quizzes, examinations, and marking, 

hence providing preciously timely manner. Certainly, the gap in GenAI utilization is vested in the 

reduction of the instructors’ time for engaging in meaningful learners’ class tasks and activities for 

the provision of constructive personalized feedback. The global education system is now 



  
 

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experiencing the dynamics in the learning and teaching processes, whilst personalized techno-

mediation takes charge at individual levels. Yet, Sengar et al. (2024) cemented that the grabbed 

GenAI technologies are trending and appraised the evolution of the 21st century. Despite the 

advantages, the integration of GenAI in pedagogies has brought undeniable challenges, particularly 

in an amalgamation of the traditional curriculum and impacting the hypothesis of learning theories, 

including constructivism and cognitivism (Renninger, 2024).  

Traditionally, human interactivity, inferences, perceptions, engagement, and learning 

materials involvement continued to be pillars for quality education, regardless of these attributes 

being currently imitated by GenAI (Folman, 2025). On a further note, the deployment and 

integration of GenAI has to stimulate and boost the cognition and constructivism processes rather 

than subsiding the actions (Nepal, 2024).  Devaki (2025) insisted that in academics, the improper 

utilization of AI distorts human intelligence, despite not being supposed to disrupt cognitive 

development. Moreover, the adaptive educational GenAI learning platforms are recognized for 

being influential and assistive to learners and instructors for engaging in getting quick solutions on 

various learning contents, fostering personalized learning paths due to supportive built-in 

interactivity interfaces (Chan, Lo & Wong, 2024). Besides, the limitations found within the GenAI 

are on learners to spare enough time for engaging in constructivist aspects, taking on the different 

learning styles and goals for comprehensive knowledge transfer optimization and retention 

(Baskara, 2024). Despite the GenAI algorithms being comprised of intelligent content for learners 

and instructors to accommodate knowledge and competence based on personalized learning 

patterns, Zhao (2024) questioned on GenAI levels for the optimization of the learners’ capabilities 

in language proficiency, reading, writing, and comprehension attributes. Instructors in HEIs, 

regardless of being scaffolded in knowledge-based or competence-based approaches, are in 

dialogue on redefining learning processes based on the speed, accuracy, and efficiency brought by 

GenAI to learners in sorting different learning activities and tasks. 

Despite the quick changes in the World of technology, classroom practices in the Higher 

Education Institutions (HEIs) have been significantly affected in terms of research, teaching, and 

learning (Singun, 2025). For example, in Korea, Jang and Choi (2025) found that the utilization of 

AI contributed to the need for paradigm shifts in education, resulting in the impacts on inequalities, 

minimal teacher influence, and the need for digital enhancements. Abbasi, Wu and Luo (2025) 

analyzed data from 2,000 HEIs students and faculty from Latin America, Asia, Europe, Africa, 

and Northen America using the regression model to explore the AI impacts on curriculum; their 

findings revealed that AI frequency usage, faculty member knowledge, institutional support on 

promoting the AI engagement in curriculum are influenced with the shortfalls including the 

personalized learning capabilities, cultural diversities, students adaptability, AIs navigation 

alignment inabilities and complexities, ethical issues educators and leaders subjectivism are leading 

AI not being recommended for education. Another comprehensive review conducted by Prather 

et al. (2025) on research papers from 2023 to 2024 on the current trends in GenAI presented new 

tools for solving computing, but also, they are disruptive to the teaching and learning theories that 

fostered implementation of the curriculum.   

 Certainly, it was insisted by Jarilkapovich (2025) on the need for implementation of the 

modern education process, focused on encompassing the technologies pedagogies innovativeness 

for students to develop the constructivist pillars of development of life skills, independent 

thinking, innovative, and creative approaches.  However, there are remarkable trending questions 



  
 

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about the intellectual gaps that are brought by GenAI in supporting the learners’ cognition and 

constructivist processes and practices (Kolade et al., 2024).  Likewise, an overwhelming discussion 

on the learners’ cognition brainwashing on too much dependence on GenAI is the vacuum that 

needs to be filled. Similarly, the integrity and authentication for GenAI integration in the research 

and projects, particularly in data analysis, reliability, and report writing, are other issues for 

discussion (Vetter et al., 2024). Certainly, Banele (2023) commented that the essentialities of the 

utilization of GenAI in teaching and learning processes have to capacitate students’ cognitive 

capabilities rather than displace them. However, the precision of GenAI practices brought wounds 

that need to be assessed. The papers in hand focused on assessing the fuzziness existing in the 

utilization of GenAI against the constructivist pillars among the selected HEIs at Dar es Salaam, 

Tanzania. Specifically, two specific objectives were addressed that are: (1) to examine the feelings 

on GenAI utilization in building the constructivism pillars, and (2) to determine the levels of 

constructivism gaps resulting from students’ views on GenAI utilization 

 

Methods 

Research Area, Sample, and Sampling 

The mixed approaches that followed the descriptive design were administered. The study 

involved 5 selected Higher Learning Institutions (HEIs) offering business studies that were 

randomly selected from Dar es Salaam City, in Tanzania. The sampled HEIs were selected as they 

are in the process of designing the restrictive rules and procedures for students and instructors to 

deploy the GenAI for undertaking the assignments and research activities. The sample frame 

consisted of two main strata, distributed into business studies module instructors and students. 

The sample size comprised 158 participants who were either delivering or studying the business 

studies modules were selected using probability and non-probability approaches. In the non-

probability sampling approach, the purposive technique was employed to select 8 instructors 

located to deliver the business studies module contents for Semester 1 of academic year 2024/25, 

Furthermore, to overcome biasness, 1 instructor from each of 5 HEI were randomized selected 

based on the criteria of being located to teach one stream, and the other 3 who were assigned the 

same module in two streams. On a further note, the sample of 150 students being distributed into 

30 from each HEI who were exposed to different GenAI usability and possession of digital devices 

was selected through a simple random sampling technique under probability approaches. 

Data Collection and Analysis 

Mixed data were collected, whereas the selected module instructors (8) were engaged in the 

collection of the qualitative data through administering the semi-structured interviews lasting for 

30 minutes, towards obtaining the responses for research objective one. Seemingly, the quantitative 

data was collected from 150 students who were exposed to the four-point ranked Likert Scale 

questionnaire, towards getting the responses for research objective two. The qualitative data were 

recorded, transcribed, coded, edited, tabulated, and analysed to obtain the patterns and cases 

through the thematic content analysis. The qualitative findings were presented by summary Tables 

and narrations of the emerging themes. Similarly, the quantitative data for research objective two 

on constructivist pillar gaps related to the utilization of GenAI were coded, edited, tabulated, and 

analyzed using Microsoft Excel, and findings were presented using Tables and Figures. Also, the 

standardization of the data collection tools was made through test-retest and amendment of the 

items, made accordingly. The sample that was involved in re-testing the data collection tools was 



  
 

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not engaged in actual data collection. Similarly, the Cronbach’s alpha on the questionnaire was 

assessed and found to be 0.81, hence considered to possess good reliability on the internal 

consistency of the items. The ethical considerations were adhered to as the respondents were asked 

to fill out the consent form for voluntary participation, pseudonyms were used to hide 

recognitions, no any kind of harm was caused, and permission for data collection was issued 

 

Result And Discussion 

Result 

The findings on the investigation are presented in the subsections on the feelings on GenAI 

utilization in building the constructivism pillars, and the levels of constructivism gaps resulting 

from students’ GenAI utilization. 

 

Feelings on GenAI Utilization in Constructivist Practices 

The findings on feelings about GenAI utilization in the constructivism pillars and practices 

among the students were collected through the guided semi-structured interview. Findings as 

summarized in Table 1, revealed the presence of conflicting feelings on the attributes of social 

interactions, authentication of the learning process, knowledge construction, metacognition 

reflection, emotional-affective, and inquiry-based learning. 

 

Table 1. Students’ feelings on GenAI utilization attributes contributed to the constructivist pillars 

Major Themes Key indicative attributes 

Social interactions Personalization learning  

Distorting triangle of learning 

Limit collaborations and networking. 

Knowledge 

construction  

Critical thinking  

Problem-solving  

Authentication  

Reliability 

Practical case scenarios  

Authentication of the 

learning Process 

Practical scenarios 

Engaging the contextual Real-life experience 

Personalization of the content 

Language 

Development 

Students develop fear in Oral Communication 

Exposure to the Vocabulary 

Fluency and punctuality in written communication 

Metacognition 

reflection  

Cognitive learning experiences 

Developing own learning strategies  

Reflections on the strengths and weaknesses of the learning 

process 

Emotional-affective Individualism learning 

Devices dependability 

Loneliness in the learning process 

Originality of constructed knowledge 



  
 

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Inquiry-based 

learning 

Eagerness to engage in deep learning 

Contextual exploration of the subject matter 

 

In order to get the internal respondents’ feelings, the question posed was What are the 

contributions of GenAI in constructivist aspects? Expressively, the findings disclosed the presence of 

conflicting feelings on the attribute of social interactions due to the use of GenAI, as it is 

considered a disruptor of the teaching and learning triangle components that are learners, 

instructors, and the learning environment, as was cited: 

… Use of GenAI led to personalization of learners and digital devices, hence distorting the traditional 

constructivism benefits obtained through multiple collaborations and interactions in the process of multiple 

sourcing knowledge creation, originally veined among instructors, peers, and the environment interactions 

(Respondent 5, Interview Session, 2025). 

 

Similarly, the investigation observed the need for instructors to develop strategies to 

capacitate learners in actively constructive learning processes. The responses to the item: How does 

the GenAI deployment contribute to the knowledge construction? Respondent mentioned: 

Instructors have to dedicate time to balance leveraging GenAI benefits parallel with constructivism and 

cognitivism … the active constructive learning approaches are based on critical thinking, problem-solving, 

and meaningful social interactions to guide understanding. (Respondent 2, Interview Session, 2025). 

 

In a similar vein, the respondents are alarmed about the authentication of GenAI vis-à-vis 

constructivist approaches in the knowledge construction, particularly focusing on the learners’ 

classroom activities, tasks, and assignments embedded into problem-solving, open-ended 

questions, and critical thinking. In responding to the item, how does GenAI ethically support the classroom 

practices? Respondents mentioned: 

Instructors need to change the modalities of the questions, activities, and tasks assigned to the learners. … 

involvement of practical case scenarios with real-life experiences based on the world contexts is essential in 

accelerating constructivism and cognition capability (Respondent 1, Interview Session, 2025). 

Also, the emphasis was made: 

… the authenticity of the learners’ activities performed in the era of GenAI is doubtful; in most cases, are 

lack originality and personalization. When learners are asked the same question in a controlled 

environment, they do mess up.  (Respondent 8, Interview Session, 2025) 

 

Correspondingly, the item about how the GenAI fosters language development was posed to the 

respondents, and the findings showed that the language of learnt content between the use of 

GenAI and without GenAI was perceived to be another fuzziness. Claims on the vocabulary, and 

fluency in written language compared to the oral presentations were demarcated as most of the 

learners were not orally capable of developing and presenting the arguments and defending 

statements in case of criticism, as was declared:  

 Learners are afraid, in that case, they will be asked to defend the same written assignment contents 

orally… In the learner’s submission, printed paperwork, the higher order of communication language is 

engaged…. are starting to buzz, become quiet and calm, when asked to present the same contents orally. 

(Respondent 3, Interview Session, 2025) 

 



  
 

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Apparently, in the aspect of metacognition reflections, the findings delineated the need for 

module instructors to encourage learners to independently engage in reflective learning practices, 

assessing the learning processes, thinking, monitoring, and motivating the understanding of the 

contents, as was declared: 

In the context that the use of GenAI is taking charge, guidance, monitoring, and supervision are key to 

ensure learners meet constructive cognitive processes compliance, design their learning strategies that will 

capacitate engaging in the reflective moment to assess the strengths and weaknesses of their learning rather 

than supplanting. (Respondent 7, interview session, 2025) 

 

Harmoniously, findings on the emotional, affective, and inquiry-based learning were 

revealed as being conflicting with the deployment of GenAI towards constructivism, as one of the 

respondents cited: - 

… Instructors had to redesign assignment items with gradually increasing contextual complexities and 

challenges that demand the engagement of higher-order thinking and creativity for stimulating the mental 

processes in knowledge and competencies creation.  (Respondent 4, interview session, 2025)  

 

Constructivists’ Gaps from Students’ Views on GenAI Utilization 

In the constructivist gaps, four dimensions were measured, including: frequencies of GenAI 

usage in learning, levels of device possession for accessing the GenAI, and popular GenAI used 

by learners. Also, the assessment on the constructivism pillars was categorized into: levels of 

GenAI deployment relative to the active-learning constructivism, GenAI against personal learning 

constructivism, and classroom social-constructivism approaches. 

 

Frequencies of GenAI Usage in Learning 

The deployment of the GenAI, as a tool supporting students in undertaking the pedagogical 

activities in the first semester of the academic year 2024-25, was measured in frequencies, whereas 

in general, the GenAI users were 135 (90%) of the selected students from involved HEIs, as shown 

in Figure 1. The findings revealed that students in HEIs are digitally conscious and highly use 

GenAI in learning perspectives. 

 
Fig. 1. Level of Students at HEIs Engaged in Utilizing GenAI for learning purposes (n=150) 

 

Levels of Students’ Device Possession for GenAI Accessibility 



  
 

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Utilization of digital technological devices has undergone abrupt positive changes in 

possession among the students in HEIs. Recently, the possession of smart mobile phones, tablets, 

and laptops has become mandatory among students and instructors in HEIs for communication 

enhancement, social-media interactions, and mediating the teaching-learning process, to mention 

a few. In assessing the diversities of on-hand devices possession installed with the GenAI among 

students, the findings disclosed that smart mobile phones were leading 125 (83%), as shown in 

Figure 2.    
Fig. 2. Levels of Learners in HEIs Digital Devices Possession for Accessing GenAI (n=150) 

 

Popular GenAI used by Students 

Understanding the diversity of GenAI utilized by students was important for the purpose 

of understanding the digital exposure status. The findings on the common GenAI deployed by the 

students from the selected HEIs are presented in Figure 3, whereas ChatGPT was the famous, 

being ranked 98(65%). 

Fig. 3. Distribution of Common GenAI Utilized by Learners in HEIs (n=150) 

 

GenAI Deployment against Constructivist Pillars 

65%

18%

7%
10%

ChatGPT   Grammarly

 QuillBot  Google Gemini



  
 

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The aspects of sources of knowledge creation, capacitating the confidence, and competences 

acquisition in learning in Figure 4 were ranked by students relative to the GenAI utilization against 

the constructivism procedures, where multiple learning material sources are encouraged.  

Fig. 4. Comparative levels of GenAI Deployment against Constructivism Pillars among the HEIs Students (n=150) 

 

GenAI utilization against Personal Learning Constructivism 

Nevertheless, the findings in Figure 5 present the findings on the usage of GenAI towards 

content screening, organizing, and contextually comprehending the module content in supporting 

the constructivist acquisition attributes. The findings disclosed that the GenAI was doing well in 

supporting the attribute of module content screening 80 (53%), while the constructivism was 

ranked higher in capacitating the contextualization of the learnt content 83 (55%).  

Fig. 5. Levels of Students’ GenAI utilization against Personal Learning Constructivism attributes (n=150) 

 

Classroom Social-Constructivism Approaches to the GenAI 

In the constructivist processes, the social interaction and learning materials are part of the 

processes to stimulate cognition towards the knowledge and competencies. In the aspect of social-

constructivism was found being doing well in the assessed attributes: levels of peers in learning 

processes 105 (70%), instructor-students interaction 120 (80%), students engagement in 

undertaking administered individual learning activities 95 (63%), students collaborating group 

assignment 107 (71%), timely provision of feedbacks 88 (57%); time spent to engage on the 

learning tasks and activities 126 (84%), collaboration and dialogue 112 (75%), motivation to drive 

the learning environment 106 (71%). However, on the side of dependability to GenAI was found 

to be less on the studied attributes as shown in Figure 6. 



  
 

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Fig. 6. Students’ Levels of Classroom Social-Constructivism attributes against GenAI in HEIs (n=150) 

 

Discussion 

GenAI utilization in building the constructivist pillars  

The findings about the conflicting feelings on GenAI utilization in building the 

constructivist pillars among the students disclose the presence of two junctures. On the one hand, 

GenAI was found to be powerful in capacitating the acquisition of multiple competencies and 

virtual interactions, as was insisted in the constructivist theory. Another finding revealed that the 

utilization of GenAI discarded the classroom social and peer interactions, among the integrative 

triangle of the teaching and learning processes components of students, instructors, and learning 

materials. According to the findings, the GenAI utilization has distorted the capacities for sharing 

and acquisition of diverse skills, knowledge, and competences among the HEIs students. 

According to the case study conducted by Ojukwu and Dlamini (2025) in South Africa, relative to 

the social constructivism theory, it was found that the deployment of GenAI in HEIs for teaching 

and learning has been redefining the teaching and learning output and rephrasing the knowledge 

processing frameworks. Subsequently, the findings justified the need for the HEIS and instructors 

to ensure there is a balance in the GenAI utilization among the learners without leading to bias, 

absorption of the negative constructivism pillars, and fostering the cognitive processes. On a 

further note, the study by Noroozi et al. (2024) emphasized that constructivist theory has been 

supportive in capacitating the pedagogical practices learning pathways compared to GenAI.  Also, 

it was insisted by Hsiao and Tang (2024) that GenAI has been fuzzy on the habitually focuses on 

individualism for being characterised by personalized learning.  

Afterward, scholars supported that the habitual use of GenAI contravened the constructivist 

pillars built on the fact that learners have to be dynamic in constructing, receiving, and handling 

knowledge (Sepriyanti & Kustati, 2024); learners had to be involved in designing, assessing, and 

developing learning processes, approaches, and outputs (Al Abri et al., 2024). This paper’s remarks 

45

30

55

43

62

24

38

44

10
5

12
0

95

10
7

88

12
6

11
2

10
6

GenAI Constructivism



  
 

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are sent to the module instructors in HEIs to appropriately guide learners in the integrative 

utilization of GenAI with the constructivist approaches to bring efficiency and effectiveness in the 

learning processes, towards the achievement of the intended curriculum objectives and goals. 

Correspondingly, other findings showed that the automated GenAI on social constructivism pillars 

perpetuated the presence of unpleasant learners’ attitudes and authentication gaps in language 

development, and distorted presentation capabilities in different learning contexts. Also, the 

findings disclosed the existence of displaced communication and language gaps among the learners 

relative to GenAI utilization across time frames in capturing and the reasonable vocabulary 

utilization, presenting clear statements, punctuations, and paragraph setting were observed during 

oral presentation compared to GenAI written presentations. The argument was made by Wibowo 

et al. (2025) that module instructors had to apply constructivism by encouraging and capacitating 

learners to engage in actionable strategies and approaches to foster linking, organizing, assimilating, 

accommodating, transferring, storing, and retraveling of the learned contents.  

Despite GenAI fostering personalized learning processes, the study by Al Abri et al. (2025) 

insisted that in teaching and learning, social interactions are valuable for enhancing and supporting 

the metacognition, reflection, and higher-order cognition acquisitions. Also, it was warned by 

Sepriyanti and Kustati (2024) that the GenAI practices are not meant for the replacement of mental 

structure capabilities. Seemingly, based on the findings, the recommendations are made to the 

instructors and learners that GenAI has been developed for catalyzing and mimicking some mental 

processes, natural language processing, and sentiment analysis rather than otherwise. Nevertheless, 

the implications are made that the utilization of GenAI without proper guidance caused hostile 

learning behaviours to the students, henceforth, distorted constructivist pillars due to the 

persistence capacity for dominating the mental processes. The researcher emphasized to the 

module instructors who are responsible for appropriately guiding learners to engage in the 

cognitive processes that are built on Cognitive Load Theory (CLT) and Cognitive Load 

Optimization (CLO) rather than only depending on retrieved information from the GenAI dataset.  

The conclusion is made to the HEIs to improve the practices through ensuring are developing 

mechanisms for monitoring the module instructors to administer the classroom activities that 

stimulate learners’ schemas to initiate the learning emotions, thoughts, and cognition activities 

initiated through interacting with the classroom tasks and activities. The recommendations are 

made to the module instructors to ensure they are providing the classroom activities that fix 

learners to engage in mixed methods, motivating, engaging, and timely provision of constructive 

feedback, rather than leaving them to typical dependence on GenAI.  

 

Constructivists’ gaps in students’ GenAI utilization  

The findings on Constructivists’ gaps from students’ GenAI utilization revealed the 

presence of a paradigm shift. Findings disclosed that a large proportion of learners, 135 (90%) out 

of 150, were using the GenAI. Furthermore, there are revolutions in the possession of handheld 

devices, whereby the smart mobile phones among students were 125 (83%) in the engaged HEIs. 

Seemingly, the ChatGPT magnitude was the highest GenAI used among the students, 98 (65%). 

The argument is made that the learners’ possession of different handheld devices has raised easier 

accessibility to GenAI and its deployment in academic perspectives. Based on the study findings, 

a large percentage of possession of handheld devices and the magnitude of using different GenAI 

clearly indicated that students in HEIs were independently engaged in the use of GenAI without 



  
 

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proper guidance on the pros and cons. However, the scholars warned against the deployment of 

GenAI tools to focus on capacitating rather than destroying education (Zlotnikova & Hlomani, 

2024). Besides, there are other warnings on heavily relying on GenAI for accessibility of learnt 

contents and research being compromised, the quality, hence instigating the HEIs’ educational 

values (Hoernig, Ilharco, Pereira & Pereira, 2024). On a further note, despite the GenAI fuzziness, 

Shaznay (2025) emphasized that module instructors and learners at HEIs need to be trained and 

equipped with valuable skills, competencies, and knowledge on emerging technologies for 

sustainability in the future labour market. The researcher provided the practice recommendations 

to the HEIs’ instructors to guide students in ethical proficiency regarding the GenAI deployment. 

Certainly, the comparative contradictory findings were obtained on the attributes of 

knowledge creation, capacitating confidence, and competencies acquisition in learning, along with 

the GenAI utilization for constructivism. The findings in the pillar of knowledge creation with 

GenAI were 30% while those of constructivist knowledge creation without GenAI were 52%. 

Further, the findings disclosed the slightly significant changes in competence acquisition along 

constructivism (28%) and GenAI (25%). Also, GenAI was performing well (45%) in assisting 

students to build confidence compared to constructivism (20%). Author of this paper insisted that 

the learning process is not inert but relatively passive and interconnected, being built on 

interpersonal interactions among the peer learners who possessed the backgrounds diversities; 

being capacitated by module instructors during the content delivering thereafter learners engaged 

and receiving; learners schedule time to engage into deep reading from different sources being 

printed and digital textbooks, manuals, and reference books to support captivity, transferring and 

stored the knowledge for future use. According to the study by Rasul et al. (2024), GenAI brought 

the dialogical dilemma in authentications of the learning processes despite its capacities in bridging 

the existing pedagogies gaps. Besides, the utilization of multiple sources and the processing of the 

content learnt are emphasized in building Self-Regulated Learning (SRL) and Self-Directed 

Learning (SDL), and autonomy as the building blocks of constructivism (Kharroubi & 

ElMediouni, 2024). Further, the utilization of GenAI in an educational perspective has been 

proven for limiting the constructivist full support, whereas the learning process is characterized by 

engaging the multiple interactions under SRL (Banihashem et al., 2022; Zajda & Zajda, 2021). The 

paper in hand provided the practice recommendations to the HEIs on the need to provide support 

to students on appropriate approaches for knowledge acquisition, competencies, and confidence-

building envisaged by constructivist theory. 

Seemingly, it was found in this study that the personal learning processes on the attributes 

of capacitation of content screening were 53% in GenAI, while constructivism 13%. Likewise, the 

module content organization in constructivism was found (32%) on the side of GenAI (30%). 

Also, the findings on the attribute of contextual comprehension of the learnt content in GenAI 

were 17% compared to constructivism 55%. According to the findings, the learners were assisted 

by the GenAI in content screening, being highly ranked. Researchers emphasized that the 

screening enabled the learners to get a clear picture of the module contents, hence stimulating 

schemata for receiving, accommodating, storing, and engaging in the retention processes in the 

long-term memory (Tarigan, Sipahutar & Harahap, 2023; Meylani, 2024; Granda et al., 2024). 

Despite the findings showing that the organization of the learnt content and comprehension 

through GenAI being at slightly different levels, there are indications of students copied and pasted 

the classroom activities text retrieved from GenAI and printed for submission without engaging 



  
 

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on thoroughly reading and reflexivity. Module instructors in HEIs are encouraged to capacitate 

and provide classroom activities to learners to engage and stimulate the self-comprehension 

attributes. Similarly, was insisted by scholars that constructivism emphasized that learners had to 

be assessed on dynamic capabilities in constructing, receiving, and handling knowledge (Sepriyanti 

& Kustati, 2024). Nonetheless, the module instructors in HEIs are encouraged to motivate 

students to comprehend and evaluate the learning analytics from multiple viewpoints, to build 

cognitive advancement. The conclusions are made to the HEIs and module instructors to make 

sure that the students are appropriately integrating the GenAI with adherence to the constructivist 

theory attributes, so as to shed light on learners’ SRL approaches in self-organizing and 

comprehending the new content relative to the existing content. Nonetheless, students from the 

HEIs had to engage in the constructivist processes whereby the social and learning materials 

interactions are part and parcel in stimulating the cognition processes in the knowledge and 

competencies acquisition.  

In the aspect of social attributes, the constructivism was found being doing well among 

HEIs learners involved in the study in comparison to the context of GenAI: levels of peers in 

learning processes 105 (70%), instructor-learner interaction 120 (80%), learners engagement in 

undertaking administered individual learning activities 95 (63%), learners collaborating in group 

assignment 107 (71%), timely provision of feedbacks 88 (57%); time spent to engage on the 

learning tasks and activities 126 (84%), collaboration and dialogue 112 (75%), motivation to drive 

the learning environment 106 (71%). A case study conducted by Khalid et al. (2025) concurred 

with the findings of this paper, as it was emphasized that the social constructivist pillars in the 

digital era have been the curriculum drivers among the students for better inclusivity, achievement, 

engagement, and utilization of the resources. Also, it was found by the study by Folman (2025) 

that human interactivity, perceptions, engagement, and learning materials involvement are 

important education pillars, despite currently being imitated by GenAI. The instructors from HEIs 

are recommended to improve the education provision practices through inspiring learners to 

engage in human interaction, most of the time, rather than overdependence on GenAI. The 

conclusions are made to the HEIs and instructors to capacitate the learners in the acquisition of 

competences for engaging in GenAI that are based on social constructivist pillars for the learning 

processes through envisioning creativity, critical thinking, self-efficacy, collaboration, and 

analytics. 

 

Conclusion 

The conclusion is made that the GenAI deployment in the teaching and learning processes 

has to ensure is integrated with the constructivism pillars, henceforth building the cognition 

attributes rather than replacing them. Also, the innovations brought by GenAI in education 

perspectives are to be illuminated as supportive in teaching and learning processes, rather than the 

displacement of module instructors’ and learners’ responsibilities. On a further note, the 

recommendations are made to module instructors and learners in HEIs to ensure there is a balance 

in the use of GenAI to support the constructivism pillars’ acquisitions. Moreover, the 

recommendations are made to the educators to develop positive attitudes towards GenAI as 

supportive tools for teaching and learning processes; and policy makers to develop policies, rules, 

procedures, and regulations to guide the adaptation and utilization of GenAI for supporting 

human cognition that are built on different education theories, including constructivism for 



  
 

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academic integrity for excellence. The recommendations are made to the scholars on the future 

research areas:  

(1) The HEIs’ instructors’ guidance approaches for students’ GenAI deployments towards 

academic excellence. 

(2) The students’ self-regulated learning approaches through GenAI: A case of selected 

secondary schools. 

(3) Can GenAI in learning be exemptible?  Analysis of the secondary schools’ take-home 

activities. 

 

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