Computer-supported collaborative learning (CSCL) has undergone significant advancements in the past two decades, revolutionizing the way learners engage with educational content and peers. This abstract explores key trends in CSCL, including the evolution of online communication and collaboration platforms, the impact of mobile technologies, the integration of data analytics, and the emergence of virtual reality (VR) and augmented reality (AR) environments. Additionally, the ongoing pandemic has accelerated the adoption of online and blended learning models, further shaping CSCL. These trends have transformed collaborative learning, allowing learners to exchange ideas, co-create knowledge, and engage in meaningful discussions. The utilization of data analytics enables personalized instruction and targeted support, enhancing learners' engagement and motivation. Immersive VR/AR environments promote active participation and deeper learning. Looking ahead, hybrid models combining face-to-face and online collaboration are likely to shape the future of CSCL. As instructional practices adapt and technology advances, creating engaging and effective learning environments remains a crucial focus in CSCL.

Pitch accuracy and rhythm errors are the most common problems encountered by erhu beginners. The traditional way of learning the erhu involves using a tuner and a metronome to improve these two issues. However, for erhu beginners, without the assistance of a teacher, it is often difficult to address these problems effectively. Therefore, this study has developed an "Intelligent Personalized Erhu Pitch and Rhythm Learning System" to help erhu learners learn to pitch and rhythm anytime and anywhere without the presence of a teacher while providing professional feedback. This system included pitch and rhythm training features. In addition to automatically generating sheet music in the MML (Music Macro Language) format, it allows the erhu learners to play along with the sheet music. After each performance, the system provides learners with expert-like comments on pitch and rhythm, respectively. The system also keeps a record of learners' practice sessions and provides appropriate encouragement and guidance based on their learning progress by creating an intelligent and personalized learning scaffold. After the development of the system, this study conducted a usability evaluation and investigated the relationship between usability and erhu playing experience. The results showed that the average for all usability dimensions was above 4.6, indicating that the system is acceptable for erhu learners. Moreover, learners with more erhu playing experience showed higher acceptance of the system compared to those with less experience in erhu.

This study attempted to explore the role of group motivation (i.e. collective efficacy) and collaborative learning behavior (i.e. group cohesion; group cognitive involvement) in students' group performance in learning computer science in computer-supported collaborative learning environment.

To accurately analyze the problems of students in learning, the composed test sheets must meet multiple assessment criteria, such as the ratio of relevant concepts to be evaluated, the average discrimination degree, difficulty degree and estimated testing time. In this paper, a heuristic approach is proposed to improve the efficiency of composing near optimal test sheets from very large item banks to meet multiple assessment criteria. From the experimental results, we conclude that our novel approach is desirable in composing near optimal test sheets from large item bank and hence can support the need of diagnosing student learning problems.

The pseudoexhaustive testing (PET) scheme is an economical approach to testing a large embedded programmable logic array (PLA). The authors propose an efficient algorithm named low overhead PET (LOPET) to partition the product lines. By applying this algorithm, both the area overhead and test length are reduced significantly.>

The untestability cube-number product (UCP), a testability measure that can accurately indicate the extra logic needed in testable programmable logic arrays (PLAs), is discussed. Two UCP-based PLA synthesis algorithms are developed. The first one is a restructuring algorithm named REST, and the other is a logic minimizer for testable PLA named LMTPLA. REST can make the restructured PLA testable by taking less extra hardware. LMTPLA is based on EXPRESSO-II and REST. It can consider the testability at the logic minimization process. In order to minimize UCP as well as the number of product terms, four strategies are developed: deleting the cubes with poor testability and reserving the cubes with good testability; giving up the primes, if necessary: partitioning the more untestable cubes into smaller cubes; and deleting the procedures which are useless in LMTPLA. REST and LMTPLA have been implemented on SUN4/260 in C language. For 40 benchmark circuits, the hardware overheads required are reduced by about 30-40%.>

A multipurpose medical diagnosis system, AEA (the acute exanthem advisor), is proposed. AEA offers a helpful environment for the diagnostician by providing reviewing, record keeping, and explanation functions. The diagnostician can use AEA as an assistant, record keeper, or education tool. It includes a statistical program to predict the number of patients who are going to have acute exanthemas. Test results show that the ability of AEA is almost the same as that of a diagnostician in diagnosing acute exanthemas.>