No abstract

No abstract

Feedback plays a central role in learning. Crucial to this is the nature and timing of the feedback. A number of studies have advocated for immediate feedback having the greater potential to influence learning outcomes. However, alternative studies have challenged this and highlighted that delayed feedback is perhaps preferable, especially when calling for more in-depth cognitive processing. This experimental study explores these two types within a Virtual Reality (VR) environment designed to facilitate the development of pre-university students' presentation skills.Participants were divided across two feedback conditions: immediate and delayed. Results showed that students in both groups made significant development in all presentation criteria across the two-week programme. Further, students perceived the environment to be an effective and motivating platform in which to practise their presentation skills. These findings are crucial as educators seek viable alternatives to provide for and enhance learning beyond the traditional confines of the classroom.

Active learning is considered by many academics as an important and effective learning strategy. Assessment is integrated in learning as a tool for learning, but traditional assessment methods often encourage surface learning (passive learning) rather than deep learning (active learning). Peer assessment is a method of motivating students, involving students discussing, marking and providing feedback on other students' work, and is one of the successful approaches which can be used to enhance deep learning. Students are required to think critically about what they are learning during the peer assessment process. Tutors' marking is usually accepted as reliable, but student peers' marking in a peer assessment process is suspect. As part of a study investigating whether peer assessment can be an accurate assessment method in a computer programming course, a novel web-based peer assessment tool has been developed. In this paper, we describe the tool and report the results of evaluating the tool through experiments involving large programming classes. The results suggest that computermediated peer assessment is a valuable assessment approach which promotes active learning and is an accurate assessment method in a programming course.

Examined in this study is the question of whether students in STEM courses perform better and have more positive perceptions than students in non-STEM courses, when both are offered in the blended format. As part of a blended learning initiative, 6 STEM and 8 non-STEM university courses were redesigned using the blended format. Students (n = 318) were surveyed on perceptions of their blended experience and courses grades were compared. Results indicated that STEM students performed significantly higher than non-STEM students; however, STEM students did not perceive their courses as positively as non-STEM students. The conclusion was that focusing blended learning course redesign in STEM fields in higher education may be advantageous, although more research is needed to confirm the findings and to investigate why student perceptions were relatively low for STEM students.

sessions. This paper reports on use of the facility during its first three years, considering the effects on pedagogy of experimental use of space and technology; this is correlated to an increase in number and variety of teaching and learning activities which, it is suggested, enhances the student experience.

This research aimed to synthesize a review of the literature and theory to develop a flipped classroom (FC) learning model to enhance 1st-year bachelor degree Thai student teacher academic achievement (AA) and problem-solving skills (PSS). The sample consisted of 90 student teachers who enrolled in the Digital Media and Learning Innovation (DMLI) course in the Elementary Education Program in the Education and Liberal Arts Faculty at Hatyai University in southern Thailand’s Songkhla province. The study used the FC model in an experimental group (S2) (n=30), while simultaneously comparing it to the control (S1) group using traditional classroom methods (n=31) and another group (S3) using problem-based learning (PBL) (n=29). The FC’s model development was reviewed by nine academic experts. The quasi-experiment took place over four weeks in March and April 2021. All instruments were evaluated by an additional five academic experts whose input evaluation was analyzed using MANOVA statistics with IBM’s® SPSS® for Windows Version 21 program. The results showed that Flipped PARSER group (S2) had AA results significantly higher than both the traditional and PBL groups. Also, S2’s results concerning their PSS were also significantly higher than S1 and S3 as well, while their student teacher satisfaction was also at the highest level. These results showed that the proposed Flipped PARSER Model excels at promoting the development of undergraduate students' motivation, academic achievement, and PSS.

In the present world of information, text classification is a more challenging process due to the larger number of training cases and feature set present in text data. One of the most difficult tasks in the text classification problem is high dimensionality of the feature space. As many real world text classifications are not modeled or too difficult to model, this paper aims at the real world text classification approach or model based on one of the properties of David Merrill's First principles of Instruction (FPI). The Objective is to introduce a method to improve text classifications effectiveness, efficiency and accuracy. In this methodology we categorizes the text using a pre-defined category group by providing them with the proper training set based on the feature of Application phase in FPI. The algorithm involves the Parsing, text categorization and text analysis. General Terms Pattern Recognition, Text Mining, et. al.