Applying Artificial Intelligence (AI) in an educational setting presents a wealth of opportunities, particularly for Open and Distance Learning (ODL) institutions. As ODL relies heavily on human-machine interactions, AI thus naturally offers open universities various means to address issues such as how do people actually learn; what constitutes effective teaching; as well as what are the advantages and limitations of computer-based systems in education. Open University Malaysia (OUM) is Malaysia’s premier ODL institution and has been operating for seven years. As an ODL institution, OUM’s operations and services are heavily anchored on a range of information and communication technologies (ICTs) that could potentially include AI. Though the implementation of AI has not been fully realised in education, OUM foresees many areas that can benefit from it, in terms of ensuring quality, improving pedagogical methods as well as enhancing the overall teaching and learning experience. In this paper, we will explore several fields whereby AI could be potentially utilised in an ODL institution, i.e. expert system for programme advising; automated scheduling of classes; marking of assignments; plagiarism detection; retaining learners and adapting to their diverse needs and backgrounds; maintenance of property; and ensuring security. OUM also anticipates that AI could provide a significant and highly intriguing paradigm shift in the deployment of ODL and that it could greatly influence the future of all open and distance learners.
[1]
Dawn G. Gregg.
E‐learning agents
,
2007
.
[2]
Philippe Cottier,et al.
Learning with the artificial sciences
,
2004,
History of Computing in Education.
[3]
Md. Rafiul Hassan,et al.
Artificial Neural Networks in Smart Homes
,
2006,
Designing Smart Homes.
[4]
Randy Goebel,et al.
Computational intelligence - a logical approach
,
1998
.
[5]
A Social-Cognitive Framework for PALs
,
2006
.
[6]
Dimitris Kalles,et al.
On Developing and Communicating User Models for Distance Learning Based on Assignment and Exam Data
,
2008
.
[7]
Alejandro Rodríguez-Ascaso,et al.
User Modeling for Attending Functional Diversity for ALL in Higher Education
,
2007,
WISE Workshops.
[8]
Daniel D. Suthers,et al.
Computer-supported collaborative learning: An historical perspective
,
2006
.
[9]
Bernie Garrett,et al.
Employing Intelligent and Adaptive Methods for Online Learning
,
2004
.
[10]
Juan Carlos Augusto,et al.
Designing Smart Homes, The Role of Artificial Intelligence
,
2006,
Designing Smart Homes.
[11]
Ali Jafari.
Conceptualizing Intelligent Agents for Teaching and Learning.
,
2002
.
[12]
D. Casey.
A Journey to Legitimacy: The Historical Development of Distance Education through Technology
,
2008
.
[13]
Hwan-Gue Cho,et al.
A source code linearization technique for detecting plagiarized programs
,
2007,
ITiCSE.