Designing a Chatbot-Enabled Laptop Diagnostic Assistant

This paper proposes a chatbot developed with deep learning techniques to help people troubleshoot operating system errors in laptops. In today's world, people can't wait for anything and expect an immediate response when they have a question because they want their problems solved quickly and completely. The system addresses the software aspect of technical laptop issues concerning a laptop's operating system. Deep learning is used to create the chatbot because it has been shown to be more accurate in selecting its response when conversing with users. The chatbot will be integrated into Telegram, an instant messaging service, and users will be able to communicate about laptop issues via Telegram

Can students' emotional states influence their assessment of lecturers' performance?

The Student Evaluation Form (SEF) is commonly used to assess lecturers’ teaching performance in the classroom. However, there are concerns that events that elicit emotion, such as students’ grades, could influence their assessment of their lecturers’ performance. Thus, we conducted a study to explore the effect of emotion-eliciting events on students’ emotional states and their assessment of lecturers’ performance. A random sample of 69 low- and high-ability students (26 control-group students and 43 experimental-group students) from Universiti Teknologi MARA, Johor, participated in this study. Two sets of questionnaires were used: the Positive and Negative Affect Scale and the SEF. The findings of the study indicate that especially for those with low ability, emotion-eliciting events affected students’ emotional states and their assessment of their lecturers’ performance

The use of information and communication technology in teaching and learning operation by academicians at higher education institution

Teaching and learning (T&L) delivery method is a main focus that every higher education institution needs to consider in their strategic planning. This is to ensure the academicians have clear teaching direction thus will result in more effective and clearer reception of knowledge by the students. T&L techniques have gone through several phases of revolution to be in line with current needs. Table 3.1 shows the comparison of education 1.0 to 4.0 as stated by Harkins (Harkins, 2008). The education revolutions show the changes of teaching and learning style from the teacher-centered learning to student-centered learning which influence the methods and technologies in T&L. Education 1.0 used traditional concept of T&L without being influenced by any technology. In education 2.0, students and academicians have been exposed with the Internet technology in T&L but it is not used widely in teaching and learning delivery method. In the education 3.0 era, the student-centered learning concept has evolved with an emphasis on the concept of constructivism. The constructivism concept encourages students to develop their knowledge from experiences with supported technologies such as Massive Open Online Course (MOOC). This concept also encourages interaction between students and educators and it supports students to share their views with educators’ intervention