Learning Process Research Articles

Effect of Mnemonics in the Teaching of Araling Panlipunan 9 on Students’ Written Assessment Scores: A One-Group Study Design

This study investigated the effectiveness of mnemonics in teaching Araling Panlipunan 9 on students’ written assessment scores. It used a one-group pretest-posttest design, a quasi-experimental design of the quantitative research methodology. The study was conducted at a National High School in Apayao, Philippines. Purposive sampling was used to select 40 Grade 9 students as participants. The researchers used a validated assessment instrument adopted from the Department of Education modules. The results showed that the students improved their scores significantly after using mnemonics in teaching, as indicated by the increase in the mean average score, the rejection of the null hypothesis, and the positive correlation between mnemonic usage and performance. The study recommended continuing to use mnemonic techniques in teaching Araling Panlipunan 9, providing remedial support to low-performing students, and promoting active student engagement in the learning process.

Kemampuan Membaca Memahami Bahasa Jerman dengan Model Pembelajaran Kooperatif Tipe Think Pair Share

Abstract. This research is a Classroom Action Research consisting of two cycles. This study aims to know the planning, process and results of learning using the Think Pair Share type cooperative learning model in improving German reading skills of class XI students of SMA Negeri 3 Makassar. The research data consisted of qualitative and quantitative data. Qualitative data was obtained through observation and quantitative data was obtained through the test results of students' German reading ability in cycle I and II. The data were analyzed using percentage technique. The results showed that the average score obtained by students in cycle I reached 67.4% and cycle II reached 80.9%. These results show that the use of Think Pair Share type learning model improve the German reading ability of students of class XI SMA Negeri 3 Makassar.Keyword: learning model, Think Pair Share, reading, German.

Immediate effects of Ramadan on objective time asleep in male youth football players from the Middle East: an interrupted time-series study

ABSTRACT Objective To examine the abrupt effects of Ramadan onset on actigraphy-based time asleep in male youth Muslim football players. Methods We adopted a quasi-experimental, interrupted time-series research design and tracked objective time asleep over a minimum of 12 consecutive nights in the two weeks prior to and immediately after Ramadan onset, respectively. Twenty-two, male academy student-athletes (chronological age range: 12.6 to 16.2 years) participated in the study (464 individual observations). Segmented generalized mixed-effects modelling estimated the effects of Ramadan onset on time asleep during the first period of night sleep only. Results Ramadan onset led to an immediate mean reduction of 89 min (95% confidence interval [CI], 54 to 123 min) in time asleep during the first period of night sleep compared to pre-Ramadan sleep patterns. Model-adjusted estimated marginal means for time asleep were ~ 5.7 h (95%CI, 5.1 to 6.2 h) before and ~ 4.2 h (95%CI, 3.6 to 4.7 h) after Ramadan onset. Night sleep interruptions resulting in two or more fragmented periods accounted for 8% (95%CI, 2 to 21%) to 19% (95%, 11 to 29%) of sleep observations before and after Ramadan onset, respectively. Conclusions The onset of Ramadan determined an abrupt reduction in time asleep of ~ 1 h 30 min in the first period of a night cycle and contributed to additional problems of heterogeneous sleep fragmentation that can impact optimal school learning and youth athlete performance development processes.

Augmented Reality in Education: A Review of Learning Outcomes and Pedagogical Implications

Purpose: The use of technology in education can either engage students actively, fostering motivation and effective learning, or result in passive learning if it fails to encourage critical thinking, meaning making, and metacognition. Materials and Methods: This concept paper conducts a comprehensive review of research on the potential of augmented reality (AR) in education. It systematically examines AR applications in various academic fields, comparing them to traditional educational technologies and teaching methods. Findings: Augmented reality (AR) exhibits significant potential to revolutionize education by transforming the learning process into a more active, effective, and meaningful experience. AR accomplishes this by providing advanced technology that allows users to interact with virtual and real-time applications, thereby immersing them in realistic educational scenarios. Across a spectrum of subjects, including Medicine, Chemistry, Mathematics, Physics, Geography, Biology, Astronomy, and History, AR offers advantages over conventional technology and traditional teaching methods. Implications to Theory, Practice and Policy: The research underscores the positive potential of AR in education and highlights its capacity to bridge the gap between technology and active, engaged learning. To fully harness these benefits, educators and researchers should address the identified limitations of AR and explore its further integration into educational practices. This paper emphasizes the need for ongoing research and innovation to optimize AR's role in education and enhance learning outcomes. Future research endeavors should concentrate on refining the implementation of AR for optimal educational impact.

Factors influencing undergraduate students’ engagement in online learning: a PLS-SEM approach

ABSTRACT Effective engagement during online learning is essential for achieving successful student outcomes. This study aims to determine the level of engagement among undergraduate students and its influencing factors during the online learning process. Data were collected from a sample of 609 undergraduate students, taken from four public and private universities in Malaysia. Results showed that undergradaute students have a moderate level of engagement during online learning. Their engagement was significantly influenced by perceptions of online learning, experiences in online learning, and online self-regulation skills, as demonstrated by the results of partial least square-structural equation modeling (PLS-SEM). These factors accounted for 63.7% of the variance in students’ engagement (R2 = .637, p < 0.01). The implications of the study were discussed.

Promoting emergent literacy skills among children at risk for specific learning disorder: general vs. Specific vs. Combined metacognitive interventions

ABSTRACT First graders with Developmental Language Disorder are considered at risk for exhibiting Specific Learning Disorder during school years. They also have deficiencies in their metacognitive skills, which leads to less effective learning processes. The current study examined, for the first time, the added value of various types of metacognitive interventions prior to an activity with an e-book for promoting language and literacy skills. Three experimental groups, each comprised of 30 first graders at risk for Specific Learning Disorder, were provided metacognitive intervention (specific, general, or combined) prior to an individual learning process with an e-book. The metacognitive interventions were designed according to the Triple A Model. Two control groups were also assigned: one control group engaged with an e-book without receiving any prior metacognitive intervention, and another followed its regular school activities. All groups were measured pre- and post-individual learning processes for language (vocabulary) and literacy (story comprehension) achievements. Results demonstrated an advantage to prior specific metacognitive intervention for promoting vocabulary as well as story comprehension measures. Although children at risk for Specific Learning Disorder tend to exhibit difficulties with generalisation processes, the combined metacognitive intervention proved to be as effective as the specific one.

Acceptance of Unified Communications and Collaboration Applications Among Students: A Case Study of University in Sumbawa Island Indonesia

Unified Communications and Collaboration (UCC) is a technology that combines conventional communication with computer technology to provide a more efficient communication platform. During the COVID-19 pandemic, UCC applications, such as Microsoft Team, Zoom Meeting, and Google Meet played major roles to support the teaching and learning process. However, the acceptance of UCC applications and their impacts on the future of teaching and learning process, especially for university students in rural areas, are concerned. Based on this, the current study aims to examine the factors that influence the acceptance of UCC applications at the University in Sumbawa Island, Indonesia using adapted theories of Unified Theory of Acceptance and Use of Technology model (UTAUT). In light, survey questionnaire was distributed online to 210 undergraduate students at the University in Sumbawa Island, Indonesia, to test seven factors, Facilitating Condition (FC), Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Motivation (MO), Collaboration (CO), and Behavioural Intention (BI) which were analysed using SPSS software. The findings reveal that PE, EE, SI, FC, MO, CO, and BI are significant factors that influence the acceptance of UCC applications. This finding will be a sound reference to improve the use of UCC applications for teaching and learning as well as help universities strategies their future teaching and learning system.

Artificial Intelligence and Business School Students’ Performance

This study is intended to find a relationship between Artificial Intelligence and Business School Students’ Performance. Data was collected from 150 Business School students at KIMEP University using questionnaires in Spring semester of 2024. Questionnaires were distributed two times: at the early beginning of the semester and at the end of the semester. During the semester, students thoroughly studied Artificial Intelligence and its functions and capacity. Additional classes on Artificial Intelligence tools were offered to students. Based on findings, the study proposes to address some positive implications of Artificial Intelligence integration in university teaching and learning globally. Artificial Intelligence has positive impact on students’ learning process. However, special ethical rules and standards must be developed and introduced due to the fact that there are increasing concerns over the risks associated with Artificial Intelligence usage and how it might affect human being further.

Whole Institution Approach: measurable and highly effective in empowering learners and educators for sustainability

AbstractWhole Institution Approaches (WIAs) to sustainability in education emphasize the strong link between the socio-physical environment and the learning processes and outcomes. However, there has been a lack of instruments for quantifying the implementation of WIAs based on the experience of learners and educators. In this article, we present the systematic development, pretesting, validation and first application of a novel WIA-Scale (learners: 13 items, educators: 15 items). As part of a large-scale assessment in Germany (school education, vocational education and higher education; n = 2,985), we apply the WIA-Scale and assess how WIAs are related to the effectiveness of sustainability learning. Based on extensive validation, the scale quality was evaluated as high. The application showed that young people who experience more sustainability in line with the WIA feel strongly more motivated and empowered by their educational institution to contribute to sustainability. Also, regression modeling revealed that WIA implementation is the strongest of various predictors of how sustainable learners act beyond the educational institution. Further, educators who experience more sustainability in line with the WIA feel considerably more motivated and report more sustainable behavior. They also view Education for Sustainable Development (ESD) as more relevant and participate more frequently in training on ESD. For future use, we provide the WIA-Scale in its original version, a 7/8-item variant and a one-item proxy. The scale may be used as a process indicator for high-quality sustainability education and as part of organizational development. Overall, the study shows that experienced WIAs are measurable and highly effective for quality sustainability learning.

Attitude matters more: the impact of perceived competence and attitudes toward science on science engagement among university students

ABSTRACT The nexus between science engagement and scientific literacy is established in the literature. However, very little, if any, delved deeper into the interplay of perceived competence, attitudes toward science, and science engagement of different groups of learners at different levels. This study explored the interaction of perceived competence, attitudes, and science engagement among university students majoring in computer science and communications and media at one of the universities in the Kyrgyz Republic. Informed by quantitative survey research design, a five-point Likert scale questionnaire with items adopted from the literature was used to collect data through a print survey from 149 participants. Data collected underwent partial least squares-structural equation modeling using SmartPLS 4. Results revealed the overall significant positive direct effect of perceived competence on attitudes toward science but not on science engagement, the positive direct effect of attitudes toward science on science engagement, and its significant indirect effect between perceived competence and science engagement. A reflection on the importance of developing, strengthening, and scaffolding positive attitudes toward science during the teaching and learning process is provided.

Pengaruh Bullying terhadap Motivasi Belajar Peserta Didik di Sekolah Dasar

Bullying refers to deviant behavior that is often carried out consciously or unconsciously. Bullying is repeated aggressive and negative behavior towards someone with the aim of hurting him. Bullying is defined as negative actions carried out by a stronger party against a weaker party through the use or non-use of tools with the aim of creating physical and emotional pressure on the weaker party. The increase in bullying cases in schools shows how worrying the current condition of education in Indonesia is. The aim of this research is to find out whether bullying behavior has a significant influence on students' learning motivation and enthusiasm for learning. We hope this can help schools know how big the impact of bullying is at school and help victims overcome the problems and risks of bullying. The method used is the Systematic Literature Review or SRL method, namely selecting each journal or previous research and getting results in the form of references for models/ideas that will be developed in the future. The results of this research show that bullying has a big influence on students' learning motivation, this is characterized by not having the courage to participate actively in the learning process and showing low interest in lessons. Bullying behavior significantly affects elementary school students' learning motivation. Students who experience bullying tend to show lower levels of motivation, loss of interest in learning, and lack of confidence in their academic abilities.

Faculty-student rapport, student engagement, and approaches to collegiate learning: exploring a mediational model

AbstractStudents value a close, supportive relationship with their professors, which has been shown to enhance their learning in higher education. However, more needs to be known about how quality faculty-student relationships shape students’ engagement and approaches to learning in higher education. In a diverse sample of 966 undergraduates from two different institutions of higher education, the current study explored the relationship between faculty-student rapport, student engagement, and deep and surface approaches to learning. Faculty-student rapport was positively correlated with student engagement (r = .50) and deep learning (r = .30), and negatively correlated with surface learning (r = -.21). Student engagement was positively correlated with deep learning (r = .70) and negatively with surface learning (r = -.32). Using multilevel modelling with students nested within classrooms, engagement was shown to mediate the effects of rapport on greater levels of deep learning (β = .31) and lower levels of surface learning (β = -.12). Although results held up across a range of demographic characteristics, some differences were noted for rapport-building among Asian American students and engagement across men versus women. These results have important implications for how faculty can engage students in the learning process by developing close, supportive relationships with their students and by extending their relationship with their students outside the classroom.

Eliminating Primacy Bias in Online Reinforcement Learning by Self-Distillation.

Excessive invalid explorations at the beginning of training lead deep reinforcement learning process to fall into the risk of overfitting, further resulting in spurious decisions, which obstruct agents in the following states and explorations. This phenomenon is termed primacy bias in online reinforcement learning. This work systematically investigates the primacy bias in online reinforcement learning, discussing the reason for primacy bias, while the characteristic of primacy bias is also analyzed. Besides, to learn a policy generalized to the following states and explorations, we develop an online reinforcement learning framework, termed self-distillation reinforcement learning (SDRL), based on knowledge distillation, allowing the agent to transfer the learned knowledge into a randomly initialized policy at regular intervals, and the new policy network is used to replace the original one in the following training. The core idea for this work is distilling knowledge from the trained policy to another policy can filter biases out, generating a more generalized policy in the learning process. Moreover, to avoid the overfitting of the new policy due to excessive distillations, we add an additional loss in the knowledge distillation process, using L2 regularization to improve the generalization, and the self-imitation mechanism is introduced to accelerate the learning on the current experiences. The results of several experiments in DMC and Atari 100k suggest the proposal has the ability to eliminate primacy bias for reinforcement learning methods, and the policy after knowledge distillation can urge agents to get higher scores more quickly.

Towards real-time earthquake forecasting in Chile: Integrating intelligent technologies and machine learning

This paper proposes an innovative approach towards real-time earthquake forecasting in Chile by integrating intelligent technologies and machine learning methods. Earthquakes pose significant risks to communities and infrastructure in Chile, making accurate and timely forecasting crucial for disaster preparedness and mitigation. Traditional forecasting methods have limitations in providing real-time insights into seismic activity. In contrast, intelligent technologies such as artificial intelligence (AI) and machine learning offer promising avenues for enhancing prediction accuracy and speed. A new earthquake forecasting method using a modified clustering approach LMSCAN(Local Maxima-based Spatio-Cluster Analysis Network) and enhanced neural network time series analysis LSTM-IC (Long Short Term Memory Inverse Correlation) is presented in this paper. This neural network-based technology has been utilized to forecast earthquakes in the Chile region, one of the countries with the largest seismic activity. This study explores the integration of intelligent systems with machine learning algorithms to analyze seismic data and predict earthquake occurrences in Chile. By leveraging historical seismic data, sensor networks, and advanced predictive models, our approach aims to provide timely warnings and insights into seismic events, thereby improving disaster response and resilience. The proposed framework holds the potential to revolutionize earthquake forecasting by enabling real-time monitoring and proactive measures to safeguard communities and infrastructure in Chile and beyond. The remarkable 95 % accuracy achieved by this model is a testament to its exceptional learning process, which sets it apart from other models. Its ability to learn and adapt to new data is unparalleled, allowing it to forecast incredibly precisely and produce highly reliable results.

The Impact of Integrating Various Digital Games in EFL Classrooms on Soft Skills Development

It is axiomatic that research in the broader field of educational technology has highlighted the capacity of digital games to engage students actively in the learning process, promoting motivation and facilitating knowledge retention. However, the specific impact of digital games on soft skills development within EFL contexts remains an underexplored area. Hence, this article investigates the impact of integrating diverse digital games into EFL classrooms on the development of soft skills among Moroccan EFL students. This quasi-experimental longitudinal study aimed to investigate the relationship between participation in an online gaming club and the development of soft skills, specifically English communication skills and critical thinking skills, over a six-month period. The hypothesis posited that engaging in online gaming activities would lead to improvements in both English communication skills and critical thinking skills among participants. The findings suggested that engagement in online gaming has a positive impact on the development of soft skills such as English communication skills and critical thinking skills. The study contributes to the broader discourse on innovative pedagogical approaches in EFL contexts, shedding light on the potential of digital games as effective tools for fostering essential skills beyond language proficiency. The implications of the research extend to educators, curriculum designers, and policymakers seeking to enhance the holistic development of students in EFL classrooms.

Students’ reading comprehension: an educational case about a methodological proposal in education

Introduction: The intention of this article is to show the experience of an eclectic proposal implementation in first grade students. Objective: To deeply know how in elementary school students are beginning to work on an ability that will become very important during their learning process, which will be the reading skill in a second language. Method: As they are developing this skill through the use of reproductive skills, in this study it is proposed to use an alternative methodology to this language development, which will be an eclectic methodological proposal with a qualitative approach, in order to take advantage of this skill acquisition process to begin growing reading comprehension and second language learning as well. Results: It could be demonstrated that an eclectic methodological proposal could help students to improve their reading comprehension. Conclusion: Teachers can feel confident about using eclectic methodologies in the classroom as it can become a success along the learning sessions.

Information Communication Technology (ICT) Integration in Teaching and Learning in Selected Rural Secondary School in Burera District, Rwanda

Studies conducted on the use of information and communication technology (ICT) in education posit its importance in all life domains, without exception to education. ICT has been a vehicle for aspiration, innovation, and quality academic achievement. This paper aimed to investigate the use of information and communication technology in the teaching and learning process at Ecole Secondaire Kagogo in Burera District, Rwanda. The study had two objectives: (1) to assess the benefits of using ICT in rural secondary schools, and (2) to examine the challenges preventing effective ICT integration in secondary schools. The study is descriptive, adopting a mixed-methods approach. Guided by the Diffusion of Innovations Theory (DOI), the study involved a population of 114 participants with a purposive sample size of 52 respondents. Data were collected through a questionnaire and interviews with teachers and school leaders. Findings revealed that ICT enables teachers to share assessments with students and deliver the lessons; helps learners engage in peer assessments and independent learning; and that school leaders use ICT to share resources. Reports identified inadequate infrastructure and a lack of professional development as barriers to the effective integration of ICT into schools. It was recommended that the required facilities, resources, and ICT gadgets be supplied for rural secondary schools so they would not still lag behind in the use of ICT in teaching and learning.

LITERACY IN A MULTIGRADE CLASS IN A RURAL SCHOOL

This paper shows results of a study carried out with a multigrade class in a rural school and focuses on a literacy teacher’s pedagogical work organization. The discussion emphasizes how the teacher – by means of a planning structure – develops activities considering heterogeneity as a factor that contributes to both teaching and learning processes. Data were collected of participatory observation and video and audio recordings which were transcribed and subject to the Content Analysis (Bardin, 2016). Results showed a permanent structure of connected pedagogical activities by means of students’ collective and individual organization in order to ensure that they learn how to read and write inclusively. Data trigger reflections upon the relevance of systematic pedagogical proposals as a possibility of structuring the literacy process while respecting heterogeneity of learning processes.

A Case Study of Digital Natives Using English Buzzword cue in Vocabulary Capacity in Second Language Acquisition in China: Challenges and Opportunities

In an age marked by rapid advancements in information technology and the widespread use of the Internet, the popularity of Internet buzzwords has become widespread and serves as one of the important forms of popular culture. However, there seems to be scant research on the relationship between popular Internet buzzwords and vocabulary capacity, especially the relationship between the use of Internet buzzwords and the vocabulary of English as a second language. To explore the relationship between the use of Internet buzzwords and English vocabulary capacity, this research will use a case study with 12 different categories of digital natives conducted through focus group interviews and semi-structured interviews to explore the use of specific Internet buzzword cue. The possible outcome is that different types of digital natives will have different views on the use of online buzzwords. Research may need to integrate the use of oral buzzwords in the context of offline to further demonstrate the relationship between the use of Internet buzzwords and the vocabulary of a second language, such as English. The research may shed light on the oral buzzword use in communication. This research focuses on how the specific English buzzword "cue" has developed into an Internet buzzword. Further, it discusses how similar Internet buzzwords have influenced the vocabulary aspects of English as a second language learning by digital natives. The study delves into the challenges faced by these learners and the opportunities presented by the use of such buzzwords in the language learning process". It is expected that this will shed light on the research aspect of internet buzzwords on language proficiency and further research on the impact of internet buzzwords in oral communication.

Data-driven fault detection framework for offshore wind-hydrogen systems

Offshore wind-hydrogen systems operate in harsh marine environments for extended periods, posing risks of low accessibility and high failure rates. This paper proposes a data-driven fault detection framework for offshore wind-hydrogen systems, aiming to promptly detect potential faults based on the system's physical parameters. The research establishes a comprehensive model based on the operating principles of offshore wind-hydrogen systems. The study uses fault injection techniques to simulate common partial faults in offshore wind-hydrogen systems and collects relevant physical parameters (such as wind turbine power generation, energy storage battery charging/discharging current, and electrolyzer hydrogen production rate). A fault detection model was constructed using a combination of Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) to enable precise detection of potential faults in the system. The established model provides theoretical support for designing, optimizing, and operating offshore wind-hydrogen systems, reducing reliance on actual experiments and lowering project risks and costs. Introducing artificial faults can evaluate the system's performance in different fault scenarios. This paper proposes a CNN-BiLSTM fault detection method that achieves automatic feature extraction and high-precision classification of time-series fault data, confirming the practicality and feasibility of offshore wind-hydrogen systems. This investigation realizes the integration of the offshore wind-hydrogen system model and deep learning, as well as a fully automated learning process from data to fault detection. By calculating and comparing results, it is verified that the framework has a high accuracy of 96.9%. This innovative research offers new methods and perspectives for enhancing the reliability and efficiency of fault detection in offshore wind-hydrogen systems.