The Role of Pedagogical Agents in Personalised Adaptive Learning: A Review
Abstract
:1. Introduction
2. Related Reviews on Pedagogical Agents in Personalised Adaptive Learning
“If the agents can do half of my routine tasks, that would be nice...as an academic, I can spend that valuable spare time for more productive activities. I don’t mind if those routine tasks are handled by agents.”
3. Research Methodology
3.1. Planning the Review
- To define the roles pedagogical agents play in PAL systems.
- To investigate the projected outcomes of including pedagogical agents in PAL environments.
Specifying the RQs
3.2. Conducting the Review
3.2.1. Search Strategy
3.2.2. Criteria for Study Selection
- Articles published between 2015 and 2022
- Articles written in English
- Articles that performed some form of real-time personalisation during learning according to the learner’s preferences
- Articles that incorporated pedagogical agents in the personalisation of learning
- Articles that appeared in conference proceedings and scholarly journals
- Books
- PowerPoint presentations or publications that just include abstracts
- Articles with inaccessible texts
- Articles in which the agent roles are not clearly established
- Articles that lack real-time personalisation
4. Agent Theories in Personalised Adaptive Learning
“an entity that functions continuously and autonomously in an environment in which other processes take place and other agents exist.”[15]
“an encapsulated computer system that is situated in some environment and that is capable of flexible, autonomous action in that environment in order to meet its design objectives.”[16]
“a system situated within and a part of an environment that senses that environment and acts on it, in pursuit of its own agenda and so as to effect what it senses in the future.”[17]
- Autonomy: the ability to exert some control over their behaviour and internal condition without the need for direct intervention.
- Reactivity: the capacity to detect changes in their surroundings and respond appropriately.
- Pro-activity: the ability to not just be reactive but also to engage in goal-directed behaviour
- Continuity: the capacity to run constantly or just when necessary,
- Social capacity: the ability to engage with other agents (through agent-communication language in a multi-agent system architecture) and humans (through natural language).
5. Discussions
5.1. Adaptive Roles
5.1.1. Adaptive Presentation
5.1.2. Adaptive Navigation
5.1.3. Adaptive Information Filtering
5.2. Intelligent Roles
5.2.1. Intelligent Tutoring
5.2.2. Intelligent Monitoring
5.2.3. Intelligent Collaborative Learning
5.3. Expected Outcomes
5.3.1. Improved Performance
5.3.2. Task Completion
5.3.3. Enhanced Engagement, Motivation, Responsibility
6. Conclusions and Future Directions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
FSLS | Felder Silverman Learning Style |
IEEE | Institute of Electrical and Electronics Engineers |
ITS | Intelligent Tutoring System |
MAS | Multi-Agent System |
MOOC | Massive Open Online Course |
PAL | Personalised Adaptive Learning |
PALS | Personalised Adaptive Learning System |
VLE | Virtual Learning Environment |
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Technologies | Description | |
---|---|---|
Adaptivity | Presentation | The adaptive presentation technology, which is derived from the field of adaptive hypermedia, delivers a non-static website that dynamically adapts to fit the learner model’s objectives, knowledge, and other preferences [20]. |
Navigation | Adaptive navigation is a technique that is also associated with adaptive hypermedia. Adaptive navigation provides assistance in an educational hyperspace by modifying the look of visible hyperlinks. The primary aim is to provide the ideal path across the learning space based on the learner model’s needs, preferences, and goals [20]. | |
Information Filtering | Information filtering arose from the field of information retrieval, and it assists a user in finding relevant information in a large body of information. In scenarios such as web searches, results are generated by sorting and filtering information based on the user’s choices. Adaptive information filtering can be either content-based or collaborative. | |
Intelligence | Monitoring | The lack of feedback from learners makes it difficult for remote teachers to customise their instructions to the learners’ requirements in e-learning. Using artificial intelligence approaches, intelligent monitoring technologies assist the remote teacher in keeping track of the learner’s reactions. Intelligent monitoring, which primarily employs data mining and machine learning, attempts to give teacher support in e-learning environments [6]. |
Collaborative Learning | Before the internet, collaborative learning technology was formed by combining Computer-Supported Collaborative Learning (CSCL) with Intelligent Tutoring Systems [6,20]. The goal of artificial intelligence approaches is to improve learning experiences through collaborative strategies such as group creation, peer aid, collaboration support, and virtual students. | |
Tutoring | Intelligent tutoring, which was originally used in ITS, tries to assist the student in the learning process by utilising artificial intelligence. Curriculum sequencing, intelligent solution analysis, and problem-solving assistance are all examples of help [6]. |
Year | Ref. | Design | Publication |
---|---|---|---|
2015 | [21] | Empirical | Knowledge-Based Systems |
[22] | Conceptual | International Journal of Knowledge and Learning | |
[23] | Empirical | International Journal of Adaptive and Innovative Systems | |
[24] | Empirical | Journal of Computer Assisted Learning | |
[25] | Empirical | Computers in Human Behavior | |
2017 | [26] | Conceptual | International Journal of Computer Applications |
[27] | Empirical | Intelligent Automation & Soft Computing | |
[28] | Conceptual | Computational Science and Its Applications—ICCSA 2017 | |
2018 | [29] | Empirical | Interservice/Industry Training, Simulation, and Education Conference |
[30] | Empirical | International Journal of STEM Education | |
[31] | Conceptual | International Conference on Computational Science and Its Applications | |
[32] | Conceptual | International Journal of Smart Education and Urban Society (IJSEUS) | |
2019 | [33] | Conceptual | Computers in Human Behavior |
[34] | Conceptual | XVIII International Conference on Data Science and Intelligent Analysis of Information | |
[35] | Conceptual | Heliyon | |
[36] | Empirical | 2019 CHI Conference on Human Factors in Computing Systems | |
2020 | [37] | Empirical | International Journal of Emerging Technology in Learning |
[38] | Conceptual | International Journal of Electrical and Computer Engineering | |
2021 | [39] | Empirical | Computers |
[40] | Empirical | International Conference on Enterprise Information Systems | |
[41] | Empirical | Australasian Journal of Educational Technology | |
[42] | Conceptual | International Conference on Computational Science and Its Applications | |
[43] | Conceptual | Proceedings - Frontiers in Education Conference, FIE | |
[44] | Empirical | Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data | |
2022 | [45] | Empirical | Computers and Education: Artificial Intelligence |
Ref. | Agent Roles | Outcomes | |||||||
---|---|---|---|---|---|---|---|---|---|
Adaptive Roles | Intelligent Roles | ||||||||
P | N | IF | M | CL | T | P | TC | E/M/R | |
[21] | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✗ |
[22] | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✓ |
[23] | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
[24] | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
[25] | ✗ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
[26] | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
[27] | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✗ |
[28] | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✗ |
[29] | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✓ | ✓ |
[30] | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✓ | ✓ |
[31] | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✗ |
[32] | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✗ |
[33] | ✓ | ✗ | ✓ | ✓ | ✗ | ✓ | ✓ | ✗ | ✓ |
[34] | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
[35] | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✗ |
[36] | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ |
[37] | ✗ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ | ✗ | ✗ |
[38] | ✗ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ | ✗ | ✗ |
[39] | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✗ |
[40] | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ |
[41] | ✗ | ✗ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ | ✗ |
[42] | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✓ |
[43] | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
[44] | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ | ✗ |
[45] | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ |
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Apoki, U.C.; Hussein, A.M.A.; Al-Chalabi, H.K.M.; Badica, C.; Mocanu, M.L. The Role of Pedagogical Agents in Personalised Adaptive Learning: A Review. Sustainability 2022, 14, 6442. https://doi.org/10.3390/su14116442
Apoki UC, Hussein AMA, Al-Chalabi HKM, Badica C, Mocanu ML. The Role of Pedagogical Agents in Personalised Adaptive Learning: A Review. Sustainability. 2022; 14(11):6442. https://doi.org/10.3390/su14116442
Chicago/Turabian StyleApoki, Ufuoma Chima, Aqeel M. Ali Hussein, Humam K. Majeed Al-Chalabi, Costin Badica, and Mihai L. Mocanu. 2022. "The Role of Pedagogical Agents in Personalised Adaptive Learning: A Review" Sustainability 14, no. 11: 6442. https://doi.org/10.3390/su14116442
APA StyleApoki, U. C., Hussein, A. M. A., Al-Chalabi, H. K. M., Badica, C., & Mocanu, M. L. (2022). The Role of Pedagogical Agents in Personalised Adaptive Learning: A Review. Sustainability, 14(11), 6442. https://doi.org/10.3390/su14116442