Keeping a Distance-Education Course Current Through eLearning and Contextual Assessment

Abstract

Abstract-Distance education is most economical when delivered to large groups of students over several years. The Open University course T396: Artificial Intelligence for Technology makes use of electronic delivery and a carefully designed assessment strategy to address the challenge of keeping the course up-to-date while remaining economically viable. Three aspects of currency are considered: academic content, organizational context, and breaking news. An electronic study guide permits new forms of interactivity and presentational styles, while allowing the course team the flexibility to maintain the academic content of the course. The organizational context of the course is maintained through integrated Web pages. An electronic conference provides news, such as course announcements, correction of errata, data files for assignments, and lists of frequently asked questions. It also enables students to participate in an extended learning community. Continuous assessment and the final project are designed to assess the students, to allow practice and experimentation, and to provide a vehicle for constructive feedback. The assessment strategy aims to maintain currency by introducing the latest contexts in which artificial intelligence is used. Detailed marking guides ensure consistent marking and demonstrable achievement of the intended learning outcomes. In a survey at the end of the course, a clear majority of students favored the use of the electronic study guide, particularly for teaching genetic algorithms, where the interactivity enabled difficult concepts to be demonstrated in a way that would not be possible on the printed page. The same survey also gave an overwhelming endorsement to the assessment strategy and the online electronic conference.

How social identification and trust influence organizational online knowledge sharing

“…As Tohidinia and Mosakhani (2010) point out, social identification, one force of social influence, has gained more attention in the workplace for group effectiveness such as cohesiveness, loyalty or productivity. Hopgood and Hirst (2007) learned that in‐depth learning is dependant on the learners recognizing the need to learn by collaboratively sharing knowledge. In fact, Chiu et al (2006) state that social identification may foster knowledge sharing in a community, since identification acts as a driver, influencing the motivation to exchange knowledge.…”

E-Learning with the Network

“…Context has both an individual and an organizational dimension. Situated and contextual learning enables more effective outcomes and drives individuals' intrinsic motivation to learn (Hopgood & Hirst, 2007). Organizational dimensions, such as technological sophistication, and the provision of infrastructural resources increase the extrinsic motivation of the learners by aligning the learning experience to the day-to-day needs of the workplace.…”

Improving End-User Programming with Situational Mashups in Web 2.0 Environment

“…There were various optimization solutions have been proposed, such as mathematics programming, genetic algorithm [22], ant colony optimization [23], cultural algorithm [24], and particle swarm optimization [25]. In the study area of search-based software engineering (SBSE) research area [26], there are many contributions for combinational optimization based on the metaheuristic mechanisms.…”