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Computer‐based video facilitates the creation of ‘movies’ recording actions on a computer screen complete with a voice‐over by the tutor. This paper describes the application of computer‐based video technology for point of need instruction on database searching. The Lotus ScreenCam software was used, being both inexpensive and readily available as part of the Lotus SmartSuite bundle. Initially, eight short movie clips were created, covering the techniques for searching PsycLIT on CD‐ROM and the ISI citation indexes via the BIDS gateway. The movie clips were made available on library PCs where students search these databases. The paper first examines educational theory to identify the role of computer‐based video within the educational framework. The movies created at Cardiff University are then described and the issues in design and implementation discussed. Finally, the effectiveness of this method of database searching instruction is explored and compared with more traditional point‐of‐need instruction techniques such as the handout, computer‐based tutorials and staff assistance.

The purpose of this paper is to develop a quantitative model of problem solving performance of students in the computer-based mathematics learning environment.

Regularized logistic regression was used to create a quantitative model of problem solving performance of students that predicts whether students can solve a mathematics problem correctly based on how well they solved other problems in the past. The usefulness of the model was evaluated by comparing the predicted probability of correct problem solving to the actual problem solving performance on the data set that was not used in the model building process.

The regularized logistic regression model showed a better predictive power than the standard Bayesian Knowledge Tracing model, the most frequently used quantitative model of student learning in the Educational Data Mining research.

Providing instructional scaffolding is critical in order to facilitate student learning. However, most computer-based learning environments use heuristics or rely on the discretion of students when they determine whether instructional scaffolding needs be provided. The predictive model of problem solving performance of students can be used as a quantitative guideline that can help make a better decision on when to provide instructional supports and guidance in the computer-based learning environment, which can potentially maximize the learning outcome of students.

This article reports on a research study conducted in the UK, exploring learners’ perceptions of the quality of computer based learning materials. With an increasing emphasis on individual and collective learning to enhance competitive advantage, it is important for managers and HRD practitioners to be able to judge the quality of ICT based learning resources to assure effective learning. Yet, this is often a difficult task and a potential barrier to the use of computer based learning. In addition, learners’ perceptions may affect the quality of learning outcomes. The article presents a learner evaluation tool, a feature of which is the use of qualitative methods to elicit learners’ experiences. Research findings suggest that the factors influencing learning could be both positive and negative, highlighting the complexity and subjectivity of such evaluation. This is an important step towards recognition of how learning might be hindered or helped within the ICT context.

The purpose of this research is to discuss a variety of empirical findings suggesting that surprise is positively related with enhanced memory recall. This opens the door for the assumption that surprising stimuli can be used in a controlled way to enhance learning.

A predictive model based on a Darwinian interpretation of this phenomenon is proposed. The model is coined CLEBS, which stands for “computer‐based learning enhanced by surprise”.

A discussion on how the model can be tested is provided in the context of a finance‐oriented Web‐based learning task, where subjects learn about investment instruments such as stocks and bonds.

Important implications are discussed, including possible applications in a variety of areas of interest to organizations in general.

This paper explores a different approach to evaluating the merits of specific technical components of computer based learning applications. A traditional double blind experimental study was implemented in a new context. A computer based Clinical Decision Simulator (CDS) system was designed and implemented incorporating an intelligent agent. This was compared to an otherwise identical system with no agent, and a group of students not using CBL systems. The results suggested that although no improvement in measurable learning outcomes could be conclusively demonstrated there was some evidence that those students using the intelligent agent system demonstrated more positive learning experiences and a deeper conceptualisation of the issues. This would suggest that a comparative multimethod experimental evaluation strategy, although complex (and not without its shortcomings) may help provide a more comprehensive analysis of students learning experience, and provide a useful picture of the student’s perceptions of CBL tools. This novel approach may be of particular relevance where the justification of a specific technological aspect of an e‐learning application is required. The value of developing and using an experimental strategy to evaluate a specific technological aspect of a computer based learning (CBL) application is discussed.

The purpose of this paper is to investigate an efficient means of estimating the ability of students solving problems in the computer-based learning environment.

Item response theory (IRT) and TrueSkill were applied to simulated and real problem solving data to estimate the ability of students solving homework problems in the massive open online course (MOOC). Based on the estimated ability, data mining models predicting whether students can correctly solve homework and quiz problems in the MOOC were developed. The predictive power of IRT- and TrueSkill-based data mining models was compared in terms of Area Under the receiver operating characteristic Curve.

The correlation between students’ ability estimated from IRT and TrueSkill was strong. In addition, IRT- and TrueSkill-based data mining models showed a comparable predictive power when the data included a large number of students. While IRT failed to estimate students’ ability and could not predict their problem solving performance when the data included a small number of students, TrueSkill did not experience such problems.

Estimating students’ ability is critical to determine the most appropriate time for providing instructional scaffolding in the computer-based learning environment. The findings of this study suggest that TrueSkill can be an efficient means for estimating the ability of students solving problems in the computer-based learning environment regardless of the number of students.

This paper focuses on the existing and potential role of electronic learning in small and medium‐sized organisations (SMEs). Innovations in information and communication technologies (ICTs) could create new forms of learning, particularly appealing to small organisations, to overcome traditional barriers such as lack of financial resources, time, expertise and facilities. The paper draws upon research, conducted in North Wales, exploring employee perceptions of and employer attitudes towards e‐learning. Small organisations in rural, peripheral regions such as North Wales can benefit from ICTs, not only to support e‐commerce, but also to access new opportunities for learning and development, beyond the often‐restricted local market. However, key findings from this research suggest that there are significant barriers to electronic learning, including the lack of hardware and software, and employer attitudes. A model is presented that identifies dimensions of, and factors influencing, e‐learning from employer and employee perspectives.

Computer‐based management education is evolving into a discipline which will affect a wide range of people both as designers and users. Management educators, in business and training organizations, will have the opportunity to deliver modules of their courses and design new learning experiences through this medium. Explores the literature with the objective of highlighting techniques which will help the designer work effectively within the constraints of the medium. It concludes by considering factors which have limited the growth of the medium and strategies which have the potential to overcome these limits.

With the growing use of technology in second language learning (L2), many techniques of incorporating digital video in L2 learning and platforms of task implementation appear in the field, however, with little, if any, research on how tasks can be designed and developed in these contexts. Based on Chapelle (2001, 2014) task design criteria, the current paper evaluates specifically the “interactivity” of task design interface and how it may contribute towards either dispersing or directing the learners' attention (Robinson, 2011) during the process of task completion in video-based L2 listening.

Using a qualitative approach – mainly focus groups and interviews – the current study evaluated a number of tasks that were used for computer-based L2 listening when digital video is the mode of presentation. The participants, i.e. English as a foreign language (EFL) teachers and learners, were presented with a number of task designs to try and evaluate.

The findings revealed that some task designs are perceived to be less interactive and can disperse the learner's attentional resources during the process of task completion. They also shed light on the importance of improving EFL teachers' current practices of task design in computer-based L2 listening.

This paper has contributed to our growing understanding of interactivity in relation to video-based learning and its task designs.

The application of technology in both its “hard” (for example through computing technology) and “soft” (for example through instructional design ) forms has enhanced the range of training methods available to practitioners. Much rhetoric has surrounded the use of techniques such as distance learning and computer‐based learning methods. The study aimed to explore the attitudes of managers to these “modern” approaches and other more “traditional” methods. A questionnaire survey of over 200 managers in organisations of all sizes and from a range of sectors was conducted. The data suggest that distance learning is not widely used as it is perceived as less effective, whereas at‐job learning, as well as being widely used is also perceived as being the most effective method. An analysis in terms of firm size revealed more similarities than differences between larger and smaller firms. The theoretical and practical implications of the results are discussed.