Effective Learning Strategies Research Articles

The Structure and Characteristics of Effective Massive Open Online Course Learning Strategies among College Students: A Qualitative Study

To enhance the development of massive open online course (MOOC) teaching and learning, prevalent methods and characteristics employed by college students in MOOC learning strategies must be investigated. This study employed the grounded theory approach to systematically encode and construct a learning strategy model for the use of MOOCs among college students in China. This study used data obtained from 57 college students and applied qualitative research coding procedures and NVivo software (version 12.0). The results revealed that the core learning strategies used by college students in MOOC learning could be categorized into cognitive, resource management, and metacognitive types. Five specific learning strategies were most frequently used: elaboration, interactive and cooperation, help-seeking, effort management, and information selection strategies. However, association and questioning strategies are infrequently employed by college students in their learning. Therefore, educators must actively guide students to expand their innovative thinking abilities by implementing these strategies.

A structural equation model of online learning: investigating self-efficacy, informal digital learning, self-regulated learning, and course satisfaction.

English as a Foreign Language (EFL) education increasingly relies on online learning, necessitating a nuanced understanding of crucial factors impacting learning experiences. This research investigates the intricate relationships among online learning self-efficacy, online self-regulated learning, informal digital learning of English (IDLE), and online course satisfaction within the unique context of EFL learners. The study involved 563 intermediate college students from various national universities in China. Structural Equation Modeling (SEM) was employed to analyze the data, providing comprehensive insights into the relationships among the identified variables. The results revealed significant insights. Both online learning self-efficacy and IDLE exhibited direct and positive influences on online course satisfaction. Furthermore, the study uncovered that online self-regulated learning acted as a partial mediator in the connection between online learning self-efficacy and IDLE with online course satisfaction. This mediation implies that learners' self-regulatory behaviors significantly affect how self-efficacy and informal digital language learning experiences impact overall satisfaction with online courses. The findings highlight the pivotal role of nurturing learners' self-efficacy beliefs, fostering IDLE, and promoting effective self-regulated learning strategies in the realm of online language learning. These initiatives are instrumental in enhancing learners' satisfaction and success in online courses. The implications of these findings for EFL instruction are substantial. By emphasizing the importance of self-efficacy, IDLE, and self-regulated learning strategies, educators can significantly contribute to creating more satisfying and successful online learning experiences for EFL students.

Hattie's Visible Learning Evaluation Model in Learning Strategies and Publication of Scientific Work of IKIP Siliwangi Students

This research aims to evaluate the application of the Hattie's Visible Learning Evaluation Model in strategy learning and the publication of scientific work sat IKIP Siliwangi. Using quantitative and qualitative data analysis methods, this research analyze student responses to sixty aspects of assessment that cover various learning elements. The results of the research identified the aspects with the highest and lowest scores from each study program, namely Guidance and Counselling (BK) and Indonesian Language and Literature Education (PBSI). These results provide in-depth insight regarding significant factors in developing effective learning strategies and supporting the publication of student scientific work such as humor, teaching strategies teacher, credibility outdoor/adventure programmes, lecturer effect, lecturer subject matter knowledge, questioning, religious campus, feedback personality, mentoring computer-assisted instruction, lecturer-students relationships, drama/art programs, study skills, extra-curricular programs, dan classroom discussion. Meanwhile, less effective factors are of concern, such as parental involvement, students control over learning, boredom, gender, use of calculators, changing school calendar, lack of sleep, moving between schools, mathematics, drugs, pre-term birth weight, ability grouping, not labeling students, ability grouping for gifted students. The implications of this research finding can be the basis for improving more optimal learning strategies in higher education environments, especially IKIP Siliwangi.

Virtual Active Learning to Maximize Knowledge Acquisition in Nursing Students: A Comparative Study.

Nursing students need to acquire knowledge through active methods that promote critical thinking and decision making. The purpose of this study is to analyze whether there are differences in the acquisition of knowledge by nursing students between active face-to-face or virtual teaching methods. In this comparative study, nursing students enrolled in the psychology course were divided into two groups: a face-to-face group that received active teaching methods and a virtual group. The virtual group was exposed to the Effective Learning Strategy (ELS), which included seminars based on video content through the Virtual Campus and answering questions using the H5P tool. In addition, participants engaged in reflection tasks on the content. Covariate data were collected, and knowledge tests were administered to both groups before and after the course. After three months, subjects were re-evaluated with a final exam to assess content retention. A total of 280 students were randomized. No differences were found in students' scores at the end of the knowledge test or in their final grades in the subject. Having study habits (b = 0.12, p = 0.03) and social support from relevant people (b = 0.09; p = 0.03) were associated with better post-intervention scores, and inversely with social support from friends (b = -0.12, p < 0.01). Final grades were inversely associated with digital safety literacy (b = -0.101, p = 0.01). No factors were associated with the scores of each group separately. The ELS virtual active learning model is as effective as face-to-face active learning methods for teaching psychology to first-year nursing students. This study was not registered.

Evaluation of the Use of Gamification in Language Learning for Students in Indonesia

Background. With the development of technology and students' preferences for digital interactions, gamification offers an attractive alternative in increasing the effectiveness of language learning. However, understanding the influence of gamification, especially on students in Indonesia, is something that has not been fully explored. Purpose. This research aims to evaluate the use of gamification in language learning for students in Indonesia. Research focus includes increasing motivation, engagement levels, and language learning outcomes. In addition, this research is intended to provide a solid foundation for the development of more innovative and effective learning strategies at the tertiary level in Indonesia. Method. This research adopts a quantitative approach with survey methods. A total of 40 Arabic student respondents from various universities in Indonesia were selected purposively. The sampling method involved distributing questionnaires via Arabic student WhatsApp groups. Data collection was carried out through a special questionnaire designed with Google Form. Data analysis refers to the Miles Huberman approach, including descriptive and inferential data processing. Results. The research results show variations in the level of student knowledge about gamification, with the majority giving positive responses. Although most students experience additional motivation, there are concerns regarding an overemphasis on the end result rather than the learning process. Conclusion. Gamification in language learning makes a positive contribution to student motivation, engagement, and enjoyment. However, the main challenge is the risk of overemphasis on the bottom line. The implementation of gamification needs to be adapted to the characteristics and needs of students, maintaining a balance between the game aspect and the essence of language learning. In conclusion, this research provides an in-depth understanding of the impact of gamification on Arabic language students in Indonesia, with the potential to provide guidance for the development of more effective language learning practices in higher education

State-Aware Deep Item Response Theory using student facial features.

This paper introduces a novel approach to Item Response Theory (IRT) by incorporating deep learning to analyze student facial expressions to enhance the prediction and understanding of student responses to test items. This research is based on the assertion that students' facial expressions offer crucial insights into their cognitive and affective states during testing, subsequently influencing their item responses. The proposed State-Aware Deep Item Response Theory (SAD-IRT) model introduces a new parameter, the student state parameter, which can be viewed as a relative subjective difficulty parameter. It is latent-regressed from students' facial features while solving test items using state-of-the-art deep learning techniques. In an experiment with 20 students, SAD-IRT boosted prediction performance in students' responses compared to prior models without the student state parameter, including standard IRT and its deep neural network implementation, while maintaining consistent predictions of student ability and item difficulty parameters. The research further illustrates the model's early prediction ability in predicting the student's response result before the student answered. This study holds substantial implications for educational assessment, laying the groundwork for more personalized and effective learning and assessment strategies that consider students' emotional and cognitive states.

The Effect of Learning Strategy and Self-Efficacy on Speaking Competence of Higher Vocational College Students: Anxiety as a Mediator

The three key affective and cognitive factors that affect language learning are learning strategy, self-efficacy, and learning anxiety. The ability to speak English is becoming more and more important, particularly among students in higher vocational colleges in China. The purpose of this study is to investigate the relationship of learning strategy, self-efficacy, learning anxiety and speaking competence among Chinese college EFL students in Heilongjiang province, China. It further seeks to understand whether anxiety acted as a mediating variable in the relationship between learning strategy and speaking competence, between self-efficacy and speaking competence. This study proposed a model that incorporates learning strategy, self-efficacy, anxiety, and speaking competence for English language learners. A survey questionnaire was used to gather data from college students. The questionnaires were sent to 493 Chinese college students. This study utilized a random sampling approach. The data analysis tools used in this survey are Process v4 and SPSS. The results showed learning strategy, learning anxiety and self-efficacy had a significant relationship with speaking competence. Anxiety mediated the relationship between self-efficacy and speaking competence, learning strategy and speaking competence. Thus when learners have a high degree of self-efficacy, they have a low level of English language anxiety and the more strategies students use, the less anxiety they have, resulting in a more excellent speaking performance.

The Impact of the Learning Mobile Application on Student Performance Using the Technology Acceptance Model

Technology is being increasingly used in education to develop various forms of media that effectively support instruction and learning. The purpose of this study is to determine the extent to which students majoring in electronics engineering education at Higher Education benefit from the use of different learning applications and how much influence they have on the overall level of student performance, by exploring the area of the correlation between the independent variable of Learning Strategy and student performance, with the consideration of the Technology Acceptance Model (TAM) as a possible mediator in this correlation. The current study utilized purposive sampling to collect a representative sample of 229 participants. The data was then analyzed using the Structural Equation Model (SEM), utilizing the Partial Least Square (PLS) method as the initial approach. The software used for this analysis was SmartPLS 4.0 and Network Analysis was conducted to determine the relationship between items in this study. Based on the results of this study, effective learning strategies and a high level of student acceptance of technology will have a positive impact on student performance or lead to improved student performance. Educational applications provide the potential to be streamlined and utilized by students through a pedagogical approach, as their user-friendly nature facilitates effective deployment.

Self-regulated learning strategies adopted by successful Chinese nursing students in the process of learning Nursing English.

As the number of foreign patients and the frequency of international academic exchanges increase, English proficiency has become increasingly essential for Chinese nurses in the treatment and nursing processes, clinical academic exchanges, and ongoing education. However, the overall English proficiency of Chinese nurses is generally inadequate, greatly depending on the English that they acquire during their nursing education. This study aims to explore the challenges encountered by Chinese EFL (English as a Foreign Language) nursing students in the process of learning Nursing English, along with the effective self-regulated learning strategies they adopt to overcome these challenges. Data were collected from nine Chinese EFL nursing students through their reflective journals and thematic analysis was applied. Data analysis revealed the variety of challenges EFL nursing students encountered, including language-related challenges, which are linguistic difficulties that relate to Nursing English learning itself, such as Nursing English vocabulary and terminology, English-to-English translation, limited listening comprehension, and the gap between textbook knowledge and its practical application; learner-related challenges, which are difficulties that affect students' emotional, affective, and mental state, primarily caused by uncertainty about the significance of Nursing English, the unexpected difficulty of Nursing English, and failing quizzes; and context-related challenges, which are difficulties relate to social, cultural, and educational context, such as insufficient learning resources, a lack of language environment, and peer pressure. To surmount these challenges, the participants adopted diverse self-regulated learning strategies, including setting goals, previewing in advance and reviewing in time, utilizing word roots, prefixes, and suffixes to facilitate vocabulary learning, repeating, practicing with sounds and writing systems, translating, highlighting and using imagery to overcome language-related challenges; believing in the usefulness and significance of Nursing English, keeping a growth mindset, enjoying Nursing English learning and teacher support and maintaining grit in learning Nursing English to overcome learner-related challenges; and integrating resources, creating supportive language environments and seeking assistance from teachers and cooperating with peers to overcome context-related challenges. Based on these findings, implications are drawn for Nursing English teachers, material designers, curriculum developers, and program designers. We suggest incorporating explicit strategy instruction into regular Nursing English education to enhance nursing students' self-regulated learning.

Multi-view Graph Convolutional Network with Spectral Component Decompose for Remote Sensing Images Classification

Automatic land cover classification from high-resolution remote sensing (RS) images remains challenging due to the complex composition of classes. Given the potential of a graph to simulate latent class composition, the latest development of graph convolutional network (GCN) has received increasing attention. However, most existing methods only use a single perspective graph structure, which largely limits their ability to capture the complementary features that would better represent the underlying data structure of images. Therefore, this paper proposes a novel multi-view GCN-based representation learning network(MvRLNet) for RS image classification. First, a superpixel-based spectral component decomposes module(SSCDM) is designed to enhance the uniqueness and homogeneity of graph nodes because the mixed superpixels may lead to miscellaneous information on graph aggregations. Second, a multi-view graph learning module(MGLM) is proposed to integrate topology and spectral graph information into a unified network with an effective feature learning strategy. Finally, the effectiveness of the proposed MvRLNet is validated on a variety datasets with different resolutions. The experimental results show that the proposed MvRLNet performs better than state-of-the-art techniques.

Using Machine Learning to Predict Heart Failure: A Comparative Analysis of Various Classification Algorithms

This study presents a comprehensive analysis of machine learning algorithms for predicting heart failure, a significant cause of morbidity and mortality worldwide. Employing a robust dataset of patient records with diverse clinical features, the performance of several widely-used classification algorithms, including K-Nearest Neighbours (KNN), Decision Trees, Support Vector Machines (SVM), Random Forests (RF), and Gaussian Naive Bayes etc. are systematically evaluated and compared. The methodology encompasses loading the dataset, data pre-processing, feature selection, model training, and validation. The performance of each algorithm is rigorously assessed using metrics such as accuracy, precision, recall, F1-score, and the area under the ROC curve with Random Forest outperforming the other classification algorithms. The study further investigates the influence of hyper-parameter tuning and cross-validation on model efficacy. Additionally, an interpretative analysis of the models, offering insights into feature importance and the clinical relevance of the prediction outcomes were provided. The findings aim to contribute to the field of medical informatics by identifying the most effective machine learning strategies for heart failure prediction, thereby facilitating early intervention and personalized patient care. This research not only underscores the potential of machine learning in healthcare but also highlights the challenges and considerations in developing reliable predictive models for complex medical conditions.

Assessment of educational technology in lactation physiology by health students.

to assess the suitability, facilitators, and barriers of using a video clip for teaching lactation physiology to health students. a cross-sectional study was conducted with online data collection at a higher education institution, using the Assistive Technology Assessment Instrument and open-ended questions. The sample consisted of 88 students. the video clip was deemed suitable in all attributes. Facilitators identified included attractiveness, musicality, and ease of access. Barriers noted were the music's speed and the necessity for prior knowledge. The video clip achieved adequate scores for interactivity (1.71), purpose (1.77), relevance (1.64), and clarity (1.77). The overall average of the attributes was 1.72. the video clip can serve as an effective learning strategy to enhance hybrid education, potentially contributing to the promotion and support of breastfeeding. However, some barriers underscore the importance of prior knowledge for a complete understanding of the content.

Lifelong-MonoDepth: Lifelong Learning for Multidomain Monocular Metric Depth Estimation.

With the rapid advancements in autonomous driving and robot navigation, there is a growing demand for lifelong learning (LL) models capable of estimating metric (absolute) depth. LL approaches potentially offer significant cost savings in terms of model training, data storage, and collection. However, the quality of RGB images and depth maps is sensor-dependent, and depth maps in the real world exhibit domain-specific characteristics, leading to variations in depth ranges. These challenges limit existing methods to LL scenarios with small domain gaps and relative depth map estimation. To facilitate lifelong metric depth learning, we identify three crucial technical challenges that require attention: 1) developing a model capable of addressing the depth scale variation through scale-aware depth learning; 2) devising an effective learning strategy to handle significant domain gaps; and 3) creating an automated solution for domain-aware depth inference in practical applications. Based on the aforementioned considerations, in this article, we present 1) a lightweight multihead framework that effectively tackles the depth scale imbalance; 2) an uncertainty-aware LL solution that adeptly handles significant domain gaps; and 3) an online domain-specific predictor selection method for real-time inference. Through extensive numerical studies, we show that the proposed method can achieve good efficiency, stability, and plasticity, leading the benchmarks by 8%-15%. The code is available at https://github.com/FreeformRobotics/Lifelong-MonoDepth.

베이지안 추론을 통한 과대-과소예측자의 학습전략 사용 및 효과판단에서의 착각 분석

The purpose of this study is to analyze the tendency of over- and under-prediction in the context of predicting test scores, and what learning strategies are used a lot by over-predictors(OPs) and how they judge their effects through conditional probability. 74 undergraduate students selected the three most frequently used and effective learning strategies respectively from the 10 strategies. 72% of students overestimated the test score, which was strong enough to reach 29% even in the fourth-tier students with the highest actual score. The mean difference is significant(t=5.06, p&lt;.001). In the conditional probability of strategies most used and judged to be effective by two types of predictors, the 'low' strategy is judged to be less effective than the high degree of use, and the 'high' strategy shows the opposite illusion. However, although the conditional probability of use differs greatly between the 'high' and 'low', the conditional probability of effect does not differ significantly. In the rate of up and down between the prior and the posterior probability, the OP has a lower posterior than the prior in both the use and effect judgment. In other words, it means that the percentage of all students who use (or judge that it is effective) is higher than that of the OPs. This was the same as 'distributed practice', and the conditional probability of use and effect of 'retrieval practice' only is slightly higher than that of all students. Contrary to expectations in the degree of use and effect judgment of the 'low' strategy, it was confirmed that students' illusion of the 'low' strategy was very serious through a Bayesian reasoning.

PEMAHAMAN MAHASISWA TERHADAP ETIKA BISNIS SYARIAH DALAM KONTEKS KURIKULUM PROGRAM STUDY BANK SYARIAH

This study can provide benefits, especially for students' understanding of Islamic business ethics in various curriculum frameworks of the Islamic Bank Study Program. By using a qualitative approach and using several research methods, among others, interviewing students and analyzing the content of curriculum materials to understand the extent to which the principles of Islamic business ethics are reflected in their perceptions and attitudes. Results show that students' understanding of Islamic business ethics is influenced by various factors, including teaching methods, financial literacy and practical experience. This variability in the level of understanding can give rise to a wide variety of challenges in effectively carrying out the values of Islamic business ethics. In the context of the curriculum, this research can provide valuable input to improve the learning process, especially in this area of Islamic business ethics. Simple applications of this research include, among others, the development of more effective learning strategies and the emphasis on positive experiences that can enhance the understanding and application of Islamic business ethics principles in the real world. Not only can this study contribute to the understanding of how the curriculum can be improved by reflecting the values of Islamic business itself to students, but this study can also provide different and in-depth perspectives on the various challenges and needs of Islamic business ethics.

Transformation Of Learner Learning: Improving Reasoning Skills Through Artificial Intelligence (AI)

The research aims to explore the potential of artificial intelligence (AI) in the context of Learning as a solution to the challenges in developing thinking skills. Through the use of AI technology, the study focuses on finding out the relationship between AI and students' ability to argue. The approach used in this research is quantitative with correlational methods. Research results show that AI in learning can be a significant catalyst for the development of critical and analytical thinking skills. Students engaged in learning environments using AI showed an improvement in problem-solving, information-analysis, and critical thinking skills so that their ability to argue improved. In addition, learning efficiency, and motivates the learners to reach their maximum potential. This research contributes to an understanding of how AI in education can have a positive impact on the development of argumentation skills. The practical implications of these findings can open the door to the development of more effective and personalized learning strategies in the future, creating a responsive and adaptive educational environment.

Participant/Avoidant Learning Approaches and Academic Performance in Cost Accounting: A Study of South-South Nigerian Federal University Students

Since most students are unaware of the various learning approaches and the best style for learning a particular course (for example, Cost Accounting), they tend to perform below their best. Also, due to the nature of cost accounting as a core accounting course, which has to do with real-work experience and computations, students tend to adopt a different learning approach in learning the course. As a result, they tend to perform below their best. The participant learning approach is an instructional method that actively involves students in their learning process. It emphasizes engagement, interaction, and hands-on experiences rather than passive reception of information. The correlation between avoidant learning strategies and students’ academic achievement in disciplines such as cost accounting is a subject of considerable interest and pertinence. The study investigated the correlation between participant/avoidant learning strategies and students’ academic achievement in cost accounting at four Federal Universities in the South-South region of Nigeria. The population consisted of 556 final-year accounting students from the accounting departments of four Federal Universities. The researchers used a descriptive research design and a randomly selected sample of 248 students. The Pearson Product Moment Correlation (PPMC) was used to analyze the association between the learning style preference of senior accounting students in cost accounting and their academic performance in the preceding semester’s final grade. The study found a significant positive correlation between participants’ learning approach and students’ academic achievement in cost accounting. Conversely, there was a significant negative correlation between the avoidant learning approach and students’ performance in cost accounting. The study recommends fostering self-motivation among students, encouraging them to seek approval from parents and instructors, and exposing them to diverse learning styles. This self-motivation is believed to facilitate the acquisition of appropriate learning strategies for effective learning. The research suggests that students who adopt an avoidant learning approach tend to perform poorly academically. To address this issue, it is recommended that instructors and fellow students discourage.

Development of Learning Strategy-based Training Programs

Education and training are key elements in developing human resources to achieve progress and success in various areas of life. In this context, the Education and Training Program (Training and Education is an abbreviation for Education and Training) becomes an important approach in meeting the learning needs and development of individual and group competencies. Developing a learning strategy-based training program (Diklat) is a strategic step in ensuring that the training provided can have a positive and effective impact on participants. In this ever-developing era, education and training have a very important role in improving the quality of human resources. Therefore, the use of appropriate learning strategies is the main key in designing training programs that are relevant and can stimulate the development of participant competencies. The method used to create this article was a quantitative approach. Meanwhile, the type of research carried out is literature review. In learning strategy-based training, training participants will also be given the opportunity to practice implementing effective learning strategies through simulations and role plays. This aims to enable them to practically understand how to manage the learning process and provide a meaningful learning experience for training participants.

The Effect of Learning Strategies According to O’Malley and Chamot On The Learning Outcomes of Arabic Students

Arabic is often considered difficult by most students therefore an appropiate strategy is needed so that students do not find it difficult. In this case, the student learning strategy is one of components that must be considered carrefully by the teacher in improving student’s Arabic learning outcomes. Student learning strategies according to O’Malley and Chamot are divided in to 3 categories, namely metacognitive, cognitive, and affective social. The purpose of this research is to find out what strategies are used by student in learning, and the influence the student learning strategies on student learning outcomes of MAN 5 Kediri. This study used a quantitative method with an ex-post facto design. The population of this study was 230 students. While the number of samples is this study were 58 students. Sampling was determined by means of Random Sampling. The results of this study reveated that the learning strategies that were mostly used by students were cognitive strategies with an average score of 57,28. While student learning outcomes belong to the medium category. The effect of metacognitive learning strategies on learning outcomes was 4,8%, the effect of cognitive learning strategies on learning outcomes was 8,3%, and the effect of affective social learning strategies on learning outcomes was 7.1%.

Analisis Kemunculan Indikator Literasi Membaca pada Lembar Kerja Peserta Didik (LKPD) Berbasis Model RADEC di SD Laboratorium Percontohan UPI Kampus Purwakarta

This study aims to analyze the occurrence of reading literacy indicators in a set of Student Worksheets (LKPD) for elementary school students (grades 2, 3, 4, and 5) based on the Read, Answer, Discuss, Explain, Create (RADEC) model at UPI Campus Purwakarta Laboratory Elementary School. A case study methodology was employed in this research. The analysis results demonstrate the dominance of Informational Texts in almost all cases, emphasizing the importance of mastering factual information in reading literacy. Personal and cultural contextual texts also play a central role in developing reading skills. On the other hand, in the cognitive process, the elements of evaluating and reflecting on information play a key role in advancing reading literacy. The research findings provide in-depth insights into the dynamics of learning in various classes and subjects. The implications of this analysis indicate the need to develop more focused and effective learning strategies, taking into account the unique characteristics of each class and subject. By expanding the scope of reading literacy understanding through diverse texts, including fiction, and integrating personal, social, and scientific dimensions, reading education at the elementary level can continue to evolve. This research serves as a starting point in the journey towards more empowered and integrated reading literacy education at UPI Campus Purwakarta Laboratory Elementary School.