The Jigsaw Design Challenge

This article highlights an innovative take on the jigsaw format, an inclusive and cooperative active learning strategy, implemented in an upper-level engineering elective course. After students complete the usual two steps of the jigsaw method—first gaining mastery in “expert groups” and then collaboratively teaching their peers in “jigsaw groups”—they then complete a third step in their jigsaw groups, in which they work together on an authentic design problem, offering a practical take on applying course content. This activity was implemented in three courses offered both in person and remotely (online only). We share how this innovation can promote learning, problem-solving, perspective sharing, and teamwork in contexts with students from different backgrounds and levels of experience.

Enhancing Students' English Language Skills through Active Learning at an Islamic University

English is the most widely used international language in the world. Mastering English skills in this modern era is, therefore, crucial. Consequently, English needs to be sufficiently taught to students of all educational levels. In response to the issue, this study aims to investigate the active learning strategy (intense involvement of students in learning processes) employed in the Faculty of Islamic Da'wah and Communication at an Islamic Institute in Lumajang, East Java. This study was designed as a case study with in-depth interviews and observations as the main data collection. The results of this study indicate that although the active learning method was successfully implemented in this faculty, the strategies and learning activities should be varied.

Jigsaw technique as an active learning strategy in Physiology for I MBBS Students

Introduction and Aim: Innovative learning strategies may be introduced along with the conventional methods to enhance active learning by the students. Jigsaw technique is a co-operative learning method, where students play a dual role as an active learner and teacher. Hence the present study aimed to introduce and assess the acceptability of the Jigsaw technique as an active learning strategy in Physiology for first year medical undergraduates. Methods: Five parent groups were formed from 30 first year medical undergraduates with six members in each group. Each member in the parent group was allotted a sub-topic in “Immunity”. Members with the same sub-topic joined to from the expert groups. After three sessions of face-face and asynchronous online discussions spanning a duration of three weeks, facilitated by faculty, the students returned to their parent groups for peer teaching and presentation. The content of the presentation was evaluated by faculty with help of a checklist. Feedback questionnaire was administered to both the students and the faculty to assess their perceptions and acceptability of Jigsaw technique. Results: Jigsaw method was addressed as an innovative method that favored active participation, high interaction and promoted communication skills and referral habits among the students. However. it was time consuming, and students expressed difficulty in adapting to the technique. Conclusion: Students consider the learning process enjoyable and effective with Jigsaw technique in Physiology. However, owing to the time consumption and its complexity it may be sparingly used in routine curriculum.

Variational Bayesian inference-based polynomial chaos expansion: Application to time-variantreliability analysis

In the time-variant systems, random variables, stochastic processes, and time parameter are regarded as the inputs of time-variant computational model. This results in an even more computationally expensive model what makes the time-variant reliability analysis a challenging task. This paper addresses the problem by presenting an active learning strategy using polynomial chaos expansion (PCE) in an augmented reliability space. We first propose a new algorithm that determines the sparse representation applying statistical threshold to determine the significant terms of the PCE model. This adaptive decision test is integrated into the variational Bayesian method, improving its accuracy and reducing convergence time. The proposed method uses a composite criterion to identify the most significant time instants and the associated training points to enrich the experimental design. By simulations, we compare the performance of the proposed method with respect to other existing time-variant reliability analysis methods.

The effect of using an active learning strategy in teaching the English language on the achievement level of primary school students: أثر استخدام استراتيجية التعلم النشط في تدريس اللغة الانجليزية على مستوى التحصيل لدى طالبات المرحلة الابتدائية

The study aimed to identify the effect of using an active learning strategy in teaching the English language on the level of achievement of primary school students. To achieve the study objectives, the researcher used the descriptive analytical approach through utilizing the questionnaire to collect data from the targeted sample. The study population included all primary stage female teachers in Bisha Governance, who account for (109) teachers, where the researcher conducted a full survey of the population. The results of the study showed that using moral incentives to promote positive behavior among primary school students leads to improving their academic achievement, active learning increases classroom interaction between teachers and primary school students. In light of the obtained results, the researcher recommended the utilization of an active learning strategy in teaching the English language, and that English teachers should continuously focus on updating their teaching techniques and methods to boost students learning.

Effect of Flipped Classroom Approach in The Teaching of A Haematology Course

Background Flipped classroom is a teaching strategy used to enhance the engagement of students in the learning process. Replacing didactic lectures with active learning strategies through flipped classroom sessions fosters independence and the opportunity for students to engage in different passive learning styles. Although many studies of the flipped classroom approach have been conducted with medical students, few have focused on the effect of flipped classroom sessions on students in other medical professional fields. The aim of this study was to assess the effect of the flipped classroom approach on the performance of medical laboratory science students in a haematology course and their perception of the flipped classroom as an active learning strategy. In addition, students’ perceptions regarding the flipped classroom as an active learning strategy were assessed. Methods Of two cohorts in haematology courses, cohort 2 attended flipped classroom sessions, whereas cohort 1 underwent traditional class sessions. Students’ learning outcomes, achievements and performance on examinations in haematology courses were assessed. In addition, a satisfaction survey was distributed to the students to evaluate their perception of the flipped classroom as a student-centred learning strategy. Results Students in cohort 2 performed significantly better in the knowledge and cognitive domains than did those in cohort 1 (p < 0.001). Cohort 2 students completed the course successfully with an average grade of 81%, and few students received low grades; in comparison, cohort 1 students completed the course with an average grade of 73%, and 7 students received a grade of F. Of students in cohort 2, 83% believed that the flipped classroom provided a better understanding of the subject matter and appropriate knowledge and skills. Conclusion The results indicate the effectiveness of flipped classroom as an active learning style in enabling students to obtain desirable knowledge and improve their academic performance. Moreover, students recognised that the flipped classroom as an active leaning style was more beneficial than the traditional teaching approach.

Increasing youth awareness of local culture through active learning

This study aims to determine the influence of practice-based active learning on students' interest and response in learning local culture in drama classes. The research was conducted at public universities in Indonesia using two active learning strategies. Qualitative methods using participatory techniques, interviews, and observations were carried out in collecting data for this study. The sample of this research is fifty drama class students. The analysis of data was done after the drama classes ended, which was marked by the process of assessing student learning outcomes through stage performances. This study showed a statistically significant increase in students' interest and response to learning local culture through collaborative learning methods and role-play in drama classroom learning. This study recommends adopting an active learning strategy in teaching local cultural materials to students. Further research is recommended on designing different active learning strategies with other variables and in different locations. Keywords: Scriptwriting; classroom drama teaching; teaching local culture; active learning.

SALAD: An Exploration of Split Active Learning based Unsupervised Network Data Stream Anomaly Detection using Autoencoders

<div>Machine learning based intrusion detection systems monitor network data streams for cyber attacks. Challenges in this space include detection of unknown attacks, adaptation to changes in the data stream such as changes in underlying behaviour, the human cost of labeling data to retrain the machine learning model and the processing and memory constraints of a real-time data stream. Failure to manage the aforementioned factors could result in missed attacks, degraded detection performance, unnecessary expense or delayed detection times. This research evaluated autoencoders, a type of feed-forward neural network, as online anomaly detectors for network data streams. The autoencoder method was combined with an active learning strategy to further reduce labeling cost and speed up training and adaptation times, resulting in a proposed Split Active Learning Anomaly Detector (SALAD) method. The proposed method was evaluated with the NSL-KDD, KDD Cup 1999, and UNSW-NB15 data sets, using the scikit-multiflow framework. Results demonstrated that a novel Adaptive Anomaly Threshold method, combined with a split active learning strategy offered superior anomaly detection performance with a labeling budget of just 20%, significantly reducing the required human expertise to annotate the network data. Processing times of the autoencoder anomaly detector method were demonstrated to be significantly lower than traditional online learning methods, allowing for greatly improved responsiveness to attacks occurring in real time. Future research areas are applying unsupervised threshold methods, multi-label classification, sample annotation, and hybrid intrusion detection.</div>