Augmented Reality (AR) Technology-Based Learning: The Effect on Physics Learning during the COVID-19 Pandemic

The COVID-19 pandemic has significantly disrupted education and has instantaneously shifted education from being conducted predominately ‘face to face’ to being totally ‘online’. For most teachers, this unexpected teaching approach has impelled them into finding ways to provide the same quality of education to their students. One way of doing this is by adopting educational technologies in learning and teaching, including the use of augmented reality (AR) technology. AR technology has been integrated into the field of physics education. In this study, the effects of AR technology on understanding of the concepts of electricity in an online learning environment for 11th-grade students was investigated. Pretest and posttest were carried out in the control group and the experimental group. The results showed that AR technology improved understanding of electrical concepts for the students in the experimental group compared to the control group, with a very significant difference between both groups. This research contributes to the development of AR technology in education, especially in relation to the teaching and learning of abstract physics concepts.

Internship Program Management Information System with Lean Management

Internship program intends to empower students with real-world knowledge, skills, and desirable attitudes by allowing them to gain hands-on experience. This study focuses on implementing lean management principles in developing a web-based information system that manages the data and processes undertaken by the students in their internship program. The system was developed using the Rapid Application Development (RAD) model which was divided into four main modules. These modules are for monitoring and supervision of the internship program. The system will help the coordinators to manage documents, the supervisor to give grades, the students to create a journal that will monitor progress, and the administrator to manage the system. To determine if the developed system is efficient and functional, trials were conducted utilizing test scenarios, test cases, and comparison table. The developed system was evaluated using a survey questionnaire based on ISO 25010 software quality model as to Product Quality. It obtained an overall mean of 4.32 with a standard deviation value of 0.666. This validates that the objectives of the study were met and achieved. Moreover, the system was able to reduce the cost and time spent from the previous process, which proves that it successfully integrated lean management principle in its design.

Student Performance Prediction Using Case Based Reasoning Knowledge Base System (CBR-KBS) Based Data Mining

Higher education management problems in delivering 100% of graduates who can satisfy business demands. In industry it is often difficult for qualified graduates to identify the appropriate means to evaluate problem - solving abilities as well as shortcomings in the evaluation of problem solving skills. This is partially due to the lack of an adequate methodology. The purpose of this paper is to provide the appropriate CBR-KBS model for predicting and evaluating the characteristics of the student's dataset so as to comply with the parameters of selection required by the university industry. Machine learning algorithms have been used in these study areas under supervision, uncompleted and uncontrolled; K-Nearest neighbor, Naïve Bayes, Decision Tree, Neural Network, Logistic Regression and Vector Support Machines. The proposed model would allow university management to make easier, more professional, experienced and industry-specific plans for the manufacturing of graduates and graduates who passed the type I and II examinations held by the employment opportunities.

Evaluating Pangasinan State University Faculty Performance Using Associative Rule Analysis

Evaluating faculty members' performance is a very complex area to study. In addition, predicting the performance of these faculty members is a very difficult and challenging task. However, the core of education is teaching and learning, and teaching-learning works to its fullest when there are effective teachers. Measuring the effectiveness of faculty members is done based on the student evaluation of faculty. This research aims to develop a model to predict the performance of the faculty members using associative rule based on the existing evaluation form used by PSU to evaluate faculty members. The model is designed to utilize the knowledge of text analytics rule capabilities that will provide great support for the decision-making of Pangasinan State University in the Philippines. The result reveals that the term good is still the top one terms occurred for all campuses followed by teaching. The results indicated that teacher/faculty members on all campuses are good teachers. Associating words reveal that "teaching good subject/topic," "explains simply" and other meaningful associated words can be utilized to evaluate the performance of the teacher. The results exposed not only the quantitative values of faculty evaluation it also exposed the qualitative opinion of the students in the performance of their faculty members. This study reveals important aspects of the faculty member's teaching performance in terms of words/association of words that will describe their teaching performance. The results can be utilized in coaching and mentoring faculty members to cope with their weaknesses. The proposed model can be utilized by Pangasinan State University to evaluate the faculty members in terms of their teaching performance by utilizing the comments/opinions of the students.

A Predictive Model Implemented in KNIME Based on Learning Analytics for Timely Decision Making in Virtual Learning Environments

The present research aims to implement a predictive model in the KNIME platform to analyze and compare the prediction of academic performance using data from a Learning Management System (LMS), identifying students at academic risk in order to generate timely and timely interventions. The CRISP-DM methodology was used, structured in six phases: Problem analysis, data analysis, data understanding, data preparation, modeling, evaluation and implementation. Based on the analysis of online learning behavior through 22 behavioral indicators observed in the LMS of the Faculty of Educational Sciences of the National University of San Agustin. These indicators are distributed in five dimensions: Academic Performance, Access, Homework, Social Aspects and Quizzes. The model has been implemented in the KNIME platform using the Simple Regression Tree Learner training algorithm. The total population consists of 30,000 student records from which a sample of 1,000 records has been taken by simple random sampling. The accuracy of the model for early prediction of students' academic performance is evaluated, the 22 observed behavioral indicators are compared with the means of academic performance in three courses. The prediction results of the implemented model are satisfactory where the mean absolute error compared to the mean of the first course was 3. 813 and with an accuracy of 89.7%, the mean absolute error compared to the mean of the second course was 2.809 with an accuracy of 94.2% and the mean absolute error compared to the mean of the third course was 2.779 with an accuracy of 93.8%. These results demonstrate that the proposed model can be used to predict students' future academic performance from an LMS data set.

Using Screen-Capture Technology to Authenticate IT Online Learning and Assessment

Assessment has always been fundamental to teaching as it aims to gauge the impact of the teaching on students learning. The current assessment in teaching computer literacy is objective assessment that focuses on making it intentional, informative, and formalized. Although this assessment is the best way when assessing large groups of students at one limited time, it has a drawback of being limited to check the knowledge of understanding terminology and recalling steps of a particular process. This study introduces a screen-capture technology based approach to performative and authentic assessment. It involved design and implementation of screen-capture assignments to assess computer maintenance skills. The sample consisted of 28 students enrolled in computer hardware and software maintenance classes. Data from students was collected through a multi-modal student survey and a semi-structured interview. The results analysis has indicated that screen-capture performative assessment promotes students’ engagement and learning level of solving real-world problems.

Innovative Classroom Strategy: Impact on Students’ Mathematics Motivation, Anxiety and Achievement in Pre-University Studies

One aspect that influences mathematics achievement is students' mathematics motivation, which is closely related to their mathematics anxiety. This study aims to incorporate a classroom intervention strategy using a brain-based teaching approach (BBTA) with technological tools to improve students' mathematics performance in pre-university studies. BBTA was used in the classroom to increase students’ mathematics interest and minimise their mathematics anxiety to increase mathematics performance. Two hundred and six (206) pre-university students were exposed to both BBTA and conventional instructions during their Statistic lessons. Questionnaire comprises of motivation and anxiety-related questions as well as pre and post mathematics tests were administered to these students. Based on the findings, students with low anxiety appeared to have more self-confidence when studying mathematics, which simultaneously improved their examination results. These two elements are critical in students' learning of mathematics because students who have low levels of anxiety and high levels of motivation in learning mathematics attain high achievement in mathematics.

Traditional and Flipped Learning: Which Enhances Students’ Academic Performance Better?

Most of the learning institutions even before the global pandemic are using a blended learning strategy. One of the most promising and leading blended-strategy today is the Flipped Classroom Model (FCM). FCM, often called as inverted classroom or reversed instruction, is a teaching model where the content of the study is given outside the classroom and homework is done inside the classroom. Previous researches yields different results when FCM is compared with traditional learning in enhancing students’ academic performance. To address the problem, a meta-analysis has been conducted. In this study, 15 articles were chosen to be meta-analyzed. The researchers used the PRISMA model in conducting the meta-analysis and the Meta-essentials for data analysis. The analysis yields a p-value of 0.000 which means that there is a statistical significant effect by the intervention FCM to the academic performance of the students. The hedges’ g value of 0.93 has a verbal interpretation of large effect. Through subgroup analysis, it was found that FCM has a positive effect on the academic performance of the students in the subjects Physics and Mathematics with a p value of 0.000. This is also true in the subgroup, Geographical Location (Eastern and Western Countries), that yields a p-value of 0.000. Further, a moderator analysis on class size and intervention duration was also conducted. A significant p-value was found on the moderator implementation duration but not significant in the moderator class size. The analysis favors the longitudinal use of Flipped Classroom Model on enhancing student’s academic performance over Traditional Lecture Model in the subjects Physics and Mathematics regardless the class size of the students and the regions where the studies were conducted.

How Can Flipped Classroom Develop Critical Thinking Skills? A Literature Review

This review aimed at providing a comprehensive overview of how the flipped classroom can give the positive effects on developing students’ critical thinking skills. Data were collected from four databases, which included Google Scholar, ResearchGate, EBSCO, and Emerald. This study synthesized the findings of 16 studies published from 2015 to 2020. The results revealed that there were many learning activities that could be designed in a flipped classroom both outside and inside the classroom so that it allowed students to be actively involved in learning, flipped classrooms could also be integrated with other learning methods and utilize various technologies to increase their effectiveness in developing students’ critical thinking skills.

A Concept Attainment Model Using Cloud-Based Mobile Learning to Enhance the Mathematical Conceptual Knowledge of Undergraduate Students

The COVID-19 situation has affected the instructional process, with both students and instructors having to adapt to the conditions that have emerged. The inclusion of online tools as part of teaching and learning is imperative, especially in mathematics courses, in order to provide knowledge and to create a learning environment as close as possible to face-to-face learning. This study focuses on the mathematical conceptual knowledge of undergraduate students using a concept attainment model. This consists of a three-phase learning process involving the presentation of information and conceptualization, a conceptual comprehension test, and an analysis of thinking strategy. It also features the implementation of cloud-based mobile learning features, including cloud learning devices, cloud learning services, and cloud learning environments as the components of the proposed instruction model. The model was evaluated by experts before being used to investigate the mathematical conceptual knowledge of undergraduate students and how pre-test scores differ from post-test scores. Descriptive statistics and t-test were used to analyze the data. The results revealed that the overall scores for the suitability of the model indicate that this approach is most suitable, and that students learning through a concept attainment model using cloud-based mobile learning obtain a higher post-test score in mathematical conceptual knowledge compared to their pre-test score, at a level of .05 statistical significance. The framework of this study can be useful for mathematics instructors or others educators when it comes to applying it in order to develop students in mathematics contexts.