Developing Computer-Based Training using the Requirements Engineering Techniques

There are several Requirements Engineering (RE) techniques have been developed to assist large projects within the RE process. However, it is still not clear if these frameworks will adequately to be useful in developing e-Learning software. The purpose of this paper is to show that the RE techniques can also fit for developing e-Learning software such as Computer-Based Training (CBT). In this context, a case study at the Food and Beverages (F&B) Division, Radisson SAS Hotel in Hamburg was taken in order to apply some of the RE techniques. The need to have a CBT for new staff at the division, led the research to focus on identifying the problem and user needs. Using the RE techniques such as Documentation Study, Interviewing, Requirements Workshop, Observation, and Prototyping is becoming a solution that helps developer in developing the CBT as needed by user afterward. This paper presents the result of using the RE methods in developing the CBT. The programming skills in developing the CBT will not be discussed in this paper. Keywords: Computer-Based Training, e-Learning software, Requirements Engineerin

Perancangan Aplikasi Multimedia Berbasis Computer Based Training (Cbt) Pada Bidang Teknik Vokasi

Beberapa tujuan penelitian pengembangan model pembelajaran Competensi Based Training (CBT) pada bidang vokasi ini adalah pengembangan perangkat pembelajaran dalam bentuk aplikasi multimedia. Sehingga dengan adanya aplikasi mulitmedia CBT ini sebagai perangkat pembelajaran agar siswa dapat mengembangkan pengetahuan dan keterampilannya yang pada gilirannya diharapkan para siswa dapat memperoleh keunggulan kompetitif dan dapat meningkatkan kualitasnya. Penelitian ini merupakan Research & Development yang terdiri atas beberapa tahapan dan yaitu: (1) tahap analisis kebutuhan; (2) Desain; (3) Pengembangan; serta dalam tahap pengembangan terdiri atas tahapan konsep (concept), perancangan (design), pengumpulan bahan (material collecting), pembuatan (assembly), tes (testing), dan distribusi (implementation). Hasil penelitian pada tahap perancangan dan pengembangan adalah, ditemukan perangkat pembelajaran CBT dalam bentuk aplikasi multimedia menggunakan Perangkat lunak 3Ds Max untuk siswa vokasi sehingga siswa belajar seperti layaknya pratikum namun dengan tampilan dan visualisasi yang menarik serta adanya backsound musik dan suara sehingga tidak membosankan

Intelligent tutoring systems research in the training systems division: Space applications

Computer-Aided Instruction (CAI) is a mature technology used to teach students in a wide variety of domains. The introduction of Artificial Intelligence (AI) technology of the field of CAI has prompted research and development efforts in an area known as Intelligent Computer-Aided Instruction (ICAI). In some cases, ICAI has been touted as a revolutionary alternative to traditional CAI. With the advent of powerful, inexpensive school computers, ICAI is emerging as a potential rival to CAI. In contrast to this, one may conceive of Computer-Based Training (CBT) systems as lying along a continuum which runs from CAI to ICAI. Although the key difference between the two is intelligence, there is not commonly accepted definition of what constitutes an intelligent instructional system

Working and Learning with Electronic Performance Support Systems: An Effectiveness Study

In this study the effectiveness of electronic performance support systems (EPSS) is reported. Some of the expected advantages of EPSS, such as an increase in productivity and improved learning are evaluated with insurance agents using laptop computers. Theoretical statements, research design and hypotheses are presented. The conclusion is that EPSS was cheaper than classroom training and had some benefits for learners, but did not produce the expected benefit of an increase in productivity

Multimedia courseware: Never mind the quality how much will it cost to develop?

This paper evaluates multimedia courseware costing techniques such as the US Airforce Interactive Courseware Method (Golas, 1993), CBT Analyst (Kearsley, 1985), CEAC (Schooley, 1988) and MEEM (Marshall, Samson, Dugard, & Scott, 1994) against the data from ten multimedia courseware developments. The Relative Error and Mean Absolute Relative Error (MARE) are calculated to allow comparison of the different methods

Reviews

Computers and Typography edited by Rosemary Sassoon, Oxford, Intellect, 1993. ISBN: 1–871516–23–4

A comparison of structured and unstructured navigation through a CBT package

The advent of hypertext has opened up new possibilities in computer-based training. The design of courseware without any predetermined structure could make the designer's task easier, and allow greater flexibility for the trainee to structure the learning environment to suit their own learning style, This investigation was concerned with the exploration of performance differences in structured and unstructured training environments. In the structured condition, subjects encountered presequenced training and practice modules. For the unstructured condition, subjects determined their own sequence of modules. It was proposed that performance may be better in the unstructured condition. The findings indicate that this depends upon individual differences in cognitive style, some styles seemingly better at exploiting the unstructured learning environment than others

Neural Speed Reading with Structural-Jump-LSTM

Recurrent neural networks (RNNs) can model natural language by sequentially 'reading' input tokens and outputting a distributed representation of each token. Due to the sequential nature of RNNs, inference time is linearly dependent on the input length, and all inputs are read regardless of their importance. Efforts to speed up this inference, known as 'neural speed reading', either ignore or skim over part of the input. We present Structural-Jump-LSTM: the first neural speed reading model to both skip and jump text during inference. The model consists of a standard LSTM and two agents: one capable of skipping single words when reading, and one capable of exploiting punctuation structure (sub-sentence separators (,:), sentence end symbols (.!?), or end of text markers) to jump ahead after reading a word. A comprehensive experimental evaluation of our model against all five state-of-the-art neural reading models shows that Structural-Jump-LSTM achieves the best overall floating point operations (FLOP) reduction (hence is faster), while keeping the same accuracy or even improving it compared to a vanilla LSTM that reads the whole text.Comment: 10 page