Students’ Performance

Arab World English Journal (AWEJ) Special Issue on CALL No.2 July, 2015     
                                                                                                                                                                      Pp. 68 –80





Online Tutorials on Advanced Writing Skills Course:
A Case Study of Distance Learning1




Karnedi
English Language and Literature Department
Faculty of Social and Political Sciences
Universitas Terbuka, Indonesia




Abstract

Writing in English at the advanced level often refers to the process of writing. As a process, it normally goes through a series of stages such as prewriting, outlining, writing, and revising. However, teaching writing within the context of distance higher education is mostly delivered through the Internet. This paper explores an online tutorial package that is specially designed for advanced level students to improve their proficiency in writing essays. For this purpose, a research question was developed: To what extent can the technology-based online tutorial help both the tutors and the students in the teaching and learning process? A critical analysis of this practice in association with the notion of admission test to an undergraduate degree programme in translation, in particular, was then followed by a detailed discussion. Conclusions drawn from this case study are in two folds; on one hand, online advanced writing course tutorials can be considered as an alternative strategy for students to their competency in writing essays which have been achieved by learning through printed self-instructional modular packages (i.e., Writing 4 course module), and on the other, the findings are closely linked to some students’ poor writing performance prior to pursuing translation core courses could have a possible impact on retention rates in the long run.

Keywords: Aadmission test advanced writing skills course, retention rate, students’ performance, online tutorial.

E-learning has become the mandatory component of all educational institutions like schools, colleges, and universities in and around the world due to the pandemic crisis of COVID-19. This deadly situation has flipped out the offline teaching process. E-learning provides an effective teaching method that brings out the best in students. To find out the student's attitude towards e-learning, primary data has been collected from national and international wise through Google forms which include the student community from various schools, colleges, and universities. This research paper aims to study the E-learning process among students who are familiar with web-based technology. It also helps to find out solutions to improve the self-study skills of students. The stratified sampling method has been adopted in this study and the sample size is 175 across the world. The findings of the study reflect the impact of E-learning, students' interest in using E-learning resources, and their performance. In conclusion, this study shows that E-learning has become quite popular among the students all over the world particularly, the lockdown period due to the COVID-19 pandemic.

The study assessed the effect of small-group learning instruction on attitudes and performance of Basic Science students in Ekiti State, Nigeria. The study adopted a quasi-experimental of pre-test, post-test research design and was carried out on 180 JSS 2 students selected from six secondary schools using purposive sampling techniques. The two instruments used for the study included: Basic Science Performance Test (BSPT) and Students' Attitudinal Scale (SAS). Five hypotheses were generated for the study and tested at 0.05 level of significance. The findings of the study revealed that small-group learning instruction had significant and positive effects on students' attitudes and performance in Basic Science. The findings also indicated that gender had no significant effect on attitude of students taught using small-group learning instruction. Based on the academic success recorded by the small group learning classrooms, it was suggested that small-group learning instruction which is more student-centered and having potential of enhancing students' attitudes toward Basic Science should be adopted as a teaching strategy in schools.

High education is an important and critical part of education all over the world. In last year, the world has been turned increasingly to online education due to the outbreak of the Covid-19 pandemic; therefore, improving this education system became an urgent matter. Online learning systems are a primal environment for acquiring educational data which can be from different sources, especially academic institutions. These data can be mainly used to analyze and extract utilizable information to help in understanding university students’ performance and identifying factors that affect it. To extract some meaningful information from these large volumes of data, academic organizations must mine the data with high accuracy. In this work, three different real datasets were selected, pre-processed, cleaned, and filtered for applying support vector machine (SVM) with multilayer perceptron kernel (MLP kernel) and optimize its parameters using simulated annealing (SA) algorithm to improve the objective function value. While examining the search space, SA has the advantage of escaping from local minima since it offers the chance for accepting the worse neighbor as a solution in a controlled manner. The results show that the designed system can determine the best SVM parameters using SA and therefore presents better model evaluation.

This study hinges on the theory of evaluation. Frequent, continuous and impartial evaluation of academic performance is vital not only for the growth of the institution but also for the growth of the individual. The perceptions of students, teachers and supervisors were evaluated to determine the competence of science teacher along instruction in Don Mariano Marcos Memorial State University (DMMMSU-NLUC), College of Education, Philippines. This research utilized a mixed descriptive-quantitative method of investigation. Using a structured survey questionnaire, the demographic profile and competence of the science teachers were measured. It was found that science teachers with less than ten training points significantly reduced their competence in terms of their personal character, teaching efficiency, general class atmosphere, and substantiality of teaching and evaluation skills. Other personal and professional demographic profiles were also found to have an influence on the competence of science teachers along instruction. These include the number of children, sex, educational attainment, length of service and workload preparation. In conclusion, it is apparent the science teachers' competence is affected by both demographic background of the educators and their personal and professional trainings. This study reveals that knowledge of specific factors that affect science teachers' competence is necessary in improving the mode of instruction, pedagogy and trainings for science teachers to ensure quality teaching.

The main research objective of this study is to examine the impact of a suggested practical programme on improving ‘Arts of English’ seniors’ translation competences at the Islamic University of Gaza (IUG) and explore their attitudes towards translation. Researchers referred to previous studies, theoretical framework and some models for classifying translation competences and subsequently developed a modified and refereed model. The results showed that ‘Arts of English’ seniors are required to have three main competences: knowledge, skills and attitudes. The researchers also prepared a programme including a handout for students, job experience, training methods and learning styles and evaluation tools. Additionally, data were collected using an assessment card with a supportive tool; self-assessment reports, and after the researchers ensured the validity and reliability of the tools the constructed programme was applied on 15 students selected randomly from the sample of the study, including 30 female students. Data collected were statistically analyzed, and the t-test independent sample and Eta square were used to measure the effect size after conducting the test of normality. After completing the programme the post assessment card results were compared with those of the pre-assessment card and there was a statistically significant improvement in the students’ performance as observed in the post assessment card. The researchers also constructed an attitude scale, and results showed that the programme had a significant impact on improving students' attitudes towards translation.

Genetic algorithm plays a significant role, as search techniques for handling complex spaces, in many fields such as artificial intelligence, engineering, robotic, etc. The genetic processes on the natural evolution principles of populations have been fairly successful at solving problems and produce optimized solution from generation to generation. This is applied in students’ quantitative data analysis to identify the most impact factor in their performance in their curriculum. The results will help the educational institutions to improve the quality of teaching after evaluating the marks achieved by the students’ in academic career. This student analysis model considers the quantitative factors such as theoretical, mathematical, practical, departmental and other departmental marks to find the most impacting factor using genetic algorithm.

Traditionally students' attendance and overall performance have been hypothesized to go hand in hand. In current study, 195 students from non-engineering background were taught a three credits core course of construction and their attendance vs performance results are empirically investigated. Further, the students' attendance and performance have also been assessed against tutors' experience to highlight students' performance in tutorials of fresh vs experienced tutors. The assessment criteria of two quizzes each 20% weight, 1 assignment of 20% weight and a mid-semester exam with 40% weight are utilized with an attendance criterion of below 75% as low attendance. The result highlights that a clear difference of 14% marks exist between the students with less than 75% attendance and the ones with 75% and above. The students with low attendance averaged at 53.35% in terms of overall marks obtained whereas the good attendance students secured 67.40% marks on average. Furthermore, in terms of fresh vs experienced tutors, students taught by fresh and less experienced tutors not only displayed better attendance but also out passed the experienced tutors' students by a difference of 4% marks in terms of overall marks. Additionally, students with high marks in sketches secured higher overall marks as compared to the ones with lower sketch marks validating the hypothesis that students with better sketches have better imagination and perceptions, a must to have skills for construction academics and architects. This study is useful for teaching professionals and encourages the use of sketches and visualisation in construction. This ongoing study will be aided by semi structured interviews with tutors and randomly selected students to highlight the underlying factors dictating this gap. The results are expected to lay foundation for better performance of students with non-engineering backgrounds in construction courses.