Collaborative Learning Model Research Articles

The effect of flipped-jigsaw learning models on ethical decision-making.

Ethical decision-making education in nursing can be taught effectively by combining different teaching models that support the visualisation of taught concepts and integrating theory into practice. The study aims to examine the effect of flipped and jigsaw learning models on ethical decision-making and ethical sensitivity in nursing. We used a nested mixed design. A pretest-posttest single-group quasi-experimental design was used in the quantitative part, and a case study method was used in the qualitative part. This study was conducted in fall semester with second-year nursing students who studied an ethics course for the first time, using two different collaborative learning models. In the quantitative part, ethical dilemma and ethical sensitivity scales were made as pre-test with 117 and post-test with 128 students. In the qualitative part, a semi-structured three focus group interviews was conducted with 16 students. After obtaining the approval of the University's ethics committee, the study was carried out after obtaining participants' informed written and verbal consent. Students' perspectives changed positively after training. This was related to six cases in section A of the Ethical Dilemma Scale. In part B, Practical Consideration (PC) and Principled Thinking (PT) mean scores were similar, showing no significant difference. For Familiarity in section C, it was determined that 68.4% of students in the pre-test and 77.3% in the post-test were familiar with similar dilemmas. The ethical sensitivity scale's total scores were in a similar range. In the qualitative stage, ethical decision-making, ethical sensitivity, ethical dilemma and the improvement process were obtained as a theme. There was an increase in the level of ethical sensitivity and familiarity with ethical dilemmas of nursing students after education. Flipped and jigsaw learning models can be used for nursing ethics courses.

Consolidation Carnival: A Case-Based Approach to Reviewing Musculoskeletal Anatomy in an Undergraduate Medical Curriculum.

Recent changes in undergraduate medical curricula have resulted in time constraints that are particularly challenging, especially when students must learn large blocks of musculoskeletal anatomy content. Consequently, students have resorted to rote memorization to cope, which counteracts our established collaborative self-directed learning model. For a 6-week musculoskeletal anatomy course, two structured case-based review sessions are described, each following the completion of two five-hour lab sessions, two on the upper extremities and two on the lower extremities. These largely self-directed review sessions consisted of 6 students rotating through 7 to 8 stations every 10 minutes where clinical cases with follow-up questions were projected on large screens. The students were expected to work collaboratively to solve the cases utilizing the prosected specimens provided and discuss the accompanying answers at the end of each case. Ninety-four per cent of the students who participated in this study agreed that the case-based review sessions provided a helpful overview of musculoskeletal anatomy content. Student performance on the open-ended, case-based musculoskeletal examination questions showed no significant difference in performance on shoulder, hand, hip, thigh, and leg questions. There was, however, a statistically significant decrease in the students' scores on a forearm question in 2021 compared to 2019. This paper describes our integrated, collaborative musculoskeletal course, including case-based review sessions, which was positively received by students as having value in reviewing the musculoskeletal content though it was not found to improve examination performance.

Distance Collaborative Learning Model as a Solution for Developing 4.0 Literacy Competencies in The Post-Pandemic Era

Distance Collaborative Learning Model as a Solution for Developing 4.0 Literacy Competencies in The Post-Pandemic Era

Hybrid Learning Model Through SIPEJAR Content as Learning Innovation in History Education Research Courses

This research and development aim to generate a hybrid learning model by incorporating SIPEJAR UM content. This collaboration aims to foster innovation and adaptation to the changing times and the digitalization era in education. The hybrid learning model, implemented in the History Education Research course, combines face-to-face and online learning. This approach enables a blended learning process that combines the advantages of both methods. The research method utilized in this research and development study is the Dick and Carey model. The data for this article was gathered through observations, interviews, and questionnaires distribution to students and lecturers. The outcome of this research and development study is a collaborative hybrid learning model that incorporates SIPEJAR UM through the provision of learning content in the History Education Research course.

Social Media Engagement and Student’s Intention in Indonesian Higher Education Using Unified Theory of Acceptance and Use of Technology

Understanding the motivations behind the use of social media in higher education is crucial for assessing its potential benefits and challenges. However, examining the contribution of social media on collaborative learning within the context of Indonesian universities holds significance due to the country’s growing digital landscape and increasing adoption of social media platforms. This research aimed to analyze proposed collaborative learning models involving social media use among Indonesian University students. The proposed models are constructed based on the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). The quantitative method used was analyzing primary data from 143 private university students in Indonesia. Data were collected using a 5-point Likert scale self-reported questionnaire of Internet Anxiety, Habit, and Performance Expectancy and Behavior Intention as well as Social Media Engagement to mediate collaborative learning. The result of this study was that Social Media Engagement and Behavior Intention significantly influence Performance Expectancy and Habit. There was also a significant influence of Internet Anxiety on behavioral intention. Thus, Collaborative Learning is significantly influenced by Social Media Engagement. These results provided insight into developing effective strategies for integrating social media into higher education.

FedHEONN: Federated and homomorphically encrypted learning method for one-layer neural networks

Federated learning (FL) is a distributed approach to developing collaborative learning models from decentralized data. This is relevant to many real applications, such as in the field of the Internet of Things, since the models can be used in edge computing devices. FL approaches are motivated by and designed to protect privacy, a highly relevant issue given current data protection regulations. Although FL methods are privacy-preserving by design, recently published papers show that privacy leaks do occur, caused by attacks designed to extract private data from information interchanged during learning. In this work, we present an FL method based on a neural network without hidden layers that incorporates homomorphic encryption (HE) to enhance robustness against the above-mentioned attacks. Unlike traditional FL methods that require multiple rounds of training for convergence, our method obtains the collaborative global model in a single training round, yielding an effective and efficient model that simplifies management of the FL training process. In addition, since our method includes HE, it is also robust against model inversion attacks. In experiments with big data sets and a large number of clients in a federated scenario, we demonstrate that use of HE does not affect the accuracy of the model, whose results are competitive with state-of-the-art machine learning models. We also show that behavior in terms of accuracy is the same for identically and non-identically distributed data scenarios.

Legitimazing of Collaborative Learning as a recommended learning model in society 5.0 era in Indonesia

A suitable learning model greatly reassurances the learning effective, learning outcomes and students’ competencies in dealing uncertainty changes in society 5.0 era. This study drives to legitimize strongly that the collaborative learning model is a suitably model which urgently to be set-off to advance students' competence in fronting the society 5.0 era in Indonesia. To achieve the research ambitions, a qualitative method which systematic literature review design was orchestrated. Research data was poised by collecting 20 previous research judgement from the internet approximately the results of collaborative learning model implementation. Data analysis performance consist of data collection, data presentation, data condensation, and drawing conclusions. The analysis fallouts: 1) Collaborative learning is a learning model which has been empirically proven to be appropriate for Indonesian English teachers to apply in society 5.0 era. 2) The application of collaborative learning model has been empirically proven to increase the students’ competencies needed in society 5.0 era, namely English communication skills, critical thinking, collaboration skills, and solving problems skills. Subsequently, this research seeks out that collaborative learning model is a recommended model to be applied by Indonesian English teachers to produce the excellence graduates to fronting the vagueness in society 5.0 era in Indonesia

Application of a Collaborative Learning Model Accompanied by Quantum Learning Strategies in Improving Class VIII Science Biology Learning Outcomes at Junior High School 2 Satap Balla

This research is a Classroom Action Research (PTK) which aims to find out whether the application of a collaborative learning model accompanied by a quantum learning strategy can improve student learning outcomes in class VIII SMP Negeri 2 Satap Balla. The subjects of this study were class VIII students of SMP Negeri 2 Satap Balla in the odd semester of the 2022/2023 school year with a total of 24 students, with details of 15 male students and 9 female students. Cycle I and cycle II were held in four meetings each including giving tests. Data collection was carried out using student learning outcomes tests at the end of each cycle, and observations at each meeting. Data were analyzed using quantitative descriptive analysis. The results showed that in the first cycle the average value was 68.33 with the completeness of class 9 students (37.5%), and the average in the second cycle was 86.66 with the completeness of the class of 21 students (87.5%) . It can be concluded that the application of a collaborative learning model accompanied by a quantum learning strategy can improve learning outcomes in class VIII Biology at SMP Negeri 2 Satap Balla.

Teacher's Perception of Environment Project-Based Collaborative Learning as Strengthening Implementation Curriculum of Merdeka

Collaborative learning based on the environment project as a differentiating model from the implementation of the curriculum of Merdeka. This study aims to obtain teacher perceptions before and after workshops on collaborative learning based on the environment project as a practice of implementing an curriculum of Merdeka in schools. Teacher perceptions are very important in increasing competency in facilitating differentiated learning of their students as 21st-century learners. This study uses an exploratory study through a qualitative approach. This research involved 19 teachers of social and exact sciences at SMAN 3 Sampang. The teachers cover the fields of Geography, Economics, Sociology, History, Mathematics, Biology, and Chemistry. Teachers were as key informant. Data were collected from October 2022 using instruments developed. The data consisted of 17 questions about project-based collaborative learning as a strengthening implementation curriculum of Merdeka. Data collection was carried out through deep interviews, observation, and filling out questionnaires. The instruments used are based on indicators of collaborative learning based on the environment project and guidelines for implementing the curriculum of Merdeka made by the Ministry of Education and Culture. The results of this study indicate that there is a significant increase in teachers' perceptions of collaborative learning based on the environment project as a strengthening implementation of the curriculum of Merdeka, which has increased from before and after participating in learning workshops. As many as 84% of teachers have mastered the flow of the project-based collaborative learning model and as many as 74% of teachers have understood the strengthening implementation of the curriculum of Merdeka. This indicates that there has been a significant change in the mastery and understanding of the exact and social teachers in applying the differentiated learning model as a form of strengthening implementation curriculum of Merdeka. In the future, it is necessary to continue training programs or workshops on the strengthening implementation of the curriculum of Merdeka with a focus on other indicators.

Adaptive Collaborative Soft Label Learning for Unsupervised Multi-View Feature Selection

Unsupervised multi-view feature selection aims to select informative features with multi-view features and unsupervised learning. It is a challenging problem due to the absence of explicit semantic supervision. Recently, graph theory and hard pseudo-label learning have been adopted to solve multi-view feature selection problems under the unsupervised learning paradigm. However, graph-based methods are difficult to support large-scale real scenarios due to the high computational complexity of graph construction. Moreover, existing methods based on hard pseudo-label learning generally result in significant information loss. In this article, we propose an Adaptive Collaborative Soft Label Learning (ACSLL) model for unsupervised multi-view feature selection. In this model, collaborative soft label learning and multi-view feature selection are integrated into a unified framework. Specifically, we learn the pseudo soft labels from each view feature by a simple and efficient method and fuse them with an adaptive weighting strategy into a joint soft label matrix. This matrix is further used for guiding the feature selection process to identify valuable features. An effective optimization strategy guaranteed with proven convergence is derived to iteratively solve this problem. Experiments demonstrate the superiority of the proposed method in both feature selection accuracy and efficiency.

ANALYSIS OF STUDENT RESPONSE TO THE IMPLEMENTATION OF THE ETHNO-FLIPPED CLASSROOM MODEL ASSISTED BY COLLABORATIVE CLOUD CLASSROOM

The ethno-flipped classroom model is a collaborative and student-centered learning model developed by integrating the flipped learning model and the ethnomathematics approach. The implementation of the ethno-flipped classroom model is assisted by Collaborative Cloud Classroom which was developed as a Learning Management System during the implementation of learning. The purpose of this study was to determine student responses to the application of the ethno-flipped classroom model assisted by Collaborative Cloud Classroom for high school students in Gunungsitoli City, Nias Island, North Sumatra Province. This research is descriptive quantitative research with data collection techniques using Likert-scale questionnaires in Small Group and Field Test. The research sample was Gunungsitoli City High School students, namely 25 students in the small group stage and 222 students in the filed test stage. The results showed that 83% of students gave a very good response at the small group stage and 85% of students gave a very good response to the application of the model at the filed test stage. The achievement of the percentage of student responses concluded that the ethno-flipped classroom model assisted by Collaborative Cloud Classroom can be further implemented in the application of other cultural contexts in future research

Improving the Effectiveness of Hybrid Learning Through the Computer-Supported Collaborative Learning Model Facing Pandemic Covid-19

Hybrid Learning using Computer Supported Collaboration Learning (CSCL) is an effort to maximize learning during the Covid-19 pandemic. This study aims to increase the effectiveness of implementing hybrid learning using CSCL in dealing with COVID-19. The research method uses qualitative case studies, and the data is processed using interactive data analysis from Miles and Huberman. The results showed: 1) CSCL learning is a very appropriate model applied to blended learning during the Covid-19 pandemic, this model is able to improve student learning outcomes, students study harder, active, focused, learn quickly, discuss and cooperate in groups, have confidence, manage learning time and help each other in their groups; 2) The CSCL model is more effective compared to conventional learning models because it can create a more active, creative and innovative learning atmosphere; 3) CSCL learning during face-to-face classes is better able to improve student performance and creativity and innovation in learning compared to implementing CSCL in online learning, because students can discuss and cooperate directly; 4) CSCL learning is able to improve student learning outcomes, this condition can be seen from the assignment scores and midle test and final test grades; 5) CSCL learning is able to improve students' ability to discuss and collaborate in groups; 6) CSCL learning is able to overcome the limited internet network in Higher Education.

Kickstart in nursing home-Nursing students experiences of a model for active and collaborative learning in clinical placement.

To explore students' experiences from a pilot project testing out a model for active, collaborative learning in first-year placement at a nursing home. There is a need for innovative learning activities and projects to improve clinical education in nursing homes. Active, collaborative approaches in placement learning may enhance students learning outcome. The study had a qualitative and explorative design, in which the experiences of students participating in the pilot were investigated through paired interviews at the end of their placement. Twenty-two students participated in the study, and data from paired interviews were analysed using qualitative content analysis. COREQ reporting guidelines were used. Three themes emerged from the analysis: (1) The learning cell as facilitator for learning; (2) Discovering learning possibilities in nursing homes and (3) Applying tools and resources for learning. The model could reduce tension and anxiety while helping the students focus on learning options and use their environment more actively for learning. Working with a learning partner seems to increase student learning through common planning, feedback and reflection. The study emphasises the importance of facilitating active learning through the scaffolding structures and configuration of the students' learning space. This study indicates the potential for introducing active and collaborative pedagogical models in clinical placement. The model can promote nursing homes as a conducive learning arena for nursing students and help prepare students for a future work role in a rapidly changing health care field. The result of the research is shared and discussed with stakeholders prior to finalising the article.

Physics Argumentation-Based Computer-Supported Collaborative Hybrid Learning to Increase Concept Mastery and Argumentation Skills

This study aims to increase the level of concept mastery and argumentation of senior high school students in Singkawang City, West Kalimantan Province, Indonesia. The Physics Argumentation-Based Computer-Supported Collaborative Hybrid Learning (PABCSCHL) model in Socio-Scientific Issues (SSI) especially on the topic of the forest fire on the peatlands has been developed with good validation categories by three pedagogical validators and three assessment validators and been implemented to 200 students. Their argumentation skill levels are measured based on Toulmin Argumentation Pattern. The syntax of the PABCSCHL model is Reading (online), Concept Building, Discussing and Debating (offline), Experiment Designing (online), and Experiment Doing (offline). The core of this model is student collaboration in arguing, debating, and experimenting. From this research, most student solution to anticipate the fire forest on peatlands is burning and waiting until the fire is extinguished perfectly (70 students), monitoring periodically that the fire is completely extinguished (60 students), and limiting the burned area by digging trenches around the site (50 students). Student solutions describe students’ understanding of solving problems posed in group discussion sessions and debates and prove their arguments with experimental data. Before implementing the model, no student has the highest level of argumentation and concept mastery. After that, 23 students have the highest level of concept mastery, and 25 students have the highest level of argumentation. The PABCSCHL model can increase the level of concept mastery and argumentation skills. This model is a new alternative hybrid learning in the post COVID-19 pandemic. Many more SSI can be learning topics to be implemented in this model.

PENGARUH MODEL PEMBELAJARAN KOLABORATIF PEMECAHAN MASALAH TERHADAP MOTIVASI DAN KEMAMPUAN PEMECAHAN MASALAH DALAM PEMBELAJARAN IPS SISWA SD DI KECAMATAN MONCONGLOE KABUPATEN MAROS

This research was conducted by giving a pretest as the initial result before being given treatment and at the end of the meeting a posttest was given as a result of the treatment. Furthermore, the data obtained was analyzed using the SPSS v.26 application by looking for the results of the normality test, homogeneity test and Independent Sample t-Test to test the hypothesis. The results of the inferential analysis of the data obtained sig. 0.000. It turns out that the value of sig. 0.000 is smaller than the probability value of 0.05 or in other words the value of 0.05 > 0.000. Then H0 is rejected and H1 is accepted, meaning that the coefficient of data analysis is significant. So it can be concluded that, there is an influence of the Problem Solving Collaborative Learning Model on Students' Motivation and Problem Solving Ability in Social Studies Learning for Elementary School Students in Moncongloe District, Maros Regency.

Deep anatomy learning for lung airway and artery-vein modeling with contrast-enhanced CT synthesis.

Endobronchial intervention requires detailed modeling of pulmonary anatomical substructure, such as lung airway and artery-vein maps, which are commonly extracted from non-contrast computed tomography (NCCT) independently using automatic segmentation approaches. We aim to make the first attempt to jointly train a CNN-based model for airway and artery-vein segmentation along with synthetic contrast-enhanced CT (CECT) generation. A multi-task framework is proposed to simultaneously generate three segmentation maps and synthesize CECTs. We first design a collaborative learning model with tissue knowledge interaction for lung airway and artery-vein segmentation. Meanwhile, a conditional adversarial training strategy is applied to generate CECTs from NCCTs guided by artery maps. Additionally, CECT identity and reconstruction help to regularize the model for plausible NCCT to CECT translation. Extensive experiments were conducted to evaluate the performance of the proposed framework based on three datasets (90 NCCTs for the airway task, 55 NCCTs for the artery-vein task and 100 CECTs for the artery task). The results demonstrate the effective improvement of our proposed method compared to other methods and configurations that can achieve more accurate segmentation maps (Dice score coefficients for these three tasks are: 93.6%, 80.7% and 82.4%, respectively) and realistic CECTs simultaneously. The ablation study further verifies the effectiveness of the components of the designed model. This study demonstrates the model potential in multi-task learning that integrates anatomically relevant segmentation and performs NCCT to CECT translation. Such an interaction approach promotes mutually for both promising segmentation results and plausible synthesis.

The effects of the smart apps creator-based jire collaborative learning model on students’ physics learning output in Gorontalo city

The research aims to analyze the effects of the Smart Apps Creator-based Jire collaborative learning model on students’ physics learning output in Gorontalo City. It was experimental research with the pre-experimental design in the form of a one-group pretest-posttest design. The population was all senior high schools, i.e., seven state senior high schools, located in Gorontalo City. Using purposive sampling, two samples, namely tenth graders from classes X MIPA 1 and X MIPA 2 SMA Negeri 4 Gorontalo and tenth graders from classes X MIPA 1 and X MIPA 2 SMA Negeri 7 Prasetya Gorontalo, were gleaned. The total number of students engaged was 112. One class acted as an experimental class, and the other class acted as the replica one. Both classes acquired the Smart Apps Creator-based Jire collaborative learning model. The Smart Apps Creator-based Jire Collaborative learning model served as the independent variable (X), while student learning output served as the dependent variable (Y). Data collection was conducted by questionnaire distribution and a learning output test. Data analyses were carried out using the simple linear regression technique. The results demonstrated the effects of the Smart Apps Creator-based Jire collaborative learning model on student learning output at a t-count of 8.208 and a 0.000 significance value under a 5% alpha. As Fh > Ft = 67.364 > 3.93, the learning model (X) had a significant effect on student learning output (Y). From the R-square, the model (X) had an effect on student learning output (Y) by 38.00%. Meanwhile, 62% were affected by other variables unresearched here.

Penerapan Model Kooperatif Tipe Jigsaw terhadap Hasil Belajar Siswa pada Materi Perpindahan Kalor di Kelas V SD Karya Budi Banda Aceh

The study is titled Application of Collaborative Puzzle Learning Model to Learning Outcomes of Heat Transfer Materials for Students of Class V SD Karya Budi Banda Aceh. The problem in this study is that teachers often use lectures in teaching, which makes students in a passive state in learning activities. The problem formulation was how to apply the jigsaw cooperative learning model to the learning outcomes of fifth grade students in SD Karya Budi Banda Aceh in heat transfer materials. The purpose of this study was to describe the learning outcomes of fifth grade students in SD Karya Budi Banda Aceh about heat transfer materials using the jigsaw puzzle model. The subjects of this study are the students of Class V, with a total of 28 students. This research method is qualitative while the research type is descriptive. Data collection techniques are performed through testing. Data analysis uses percentage formulas. After analyzing the data, the result obtained is 89.00%. According to the results of the study, it was concluded that the application of the jigsaw cooperative model to heat transfer material could achieve complete student learning outcomes.Keywords: Jigsaw Type Cooperative Model, Learning Outcomes, Heat Transfer Materials, Science

Deep Transfer Learning: A Novel Collaborative Learning Model for Cyberattack Detection Systems in IoT Networks

Federated Learning (FL) has recently become an effective approach for cyberattack detection systems, especially in Internet-of-Things (IoT) networks. By distributing the learning process across IoT gateways, FL can improve learning efficiency, reduce communication overheads and enhance privacy for cyberattack detection systems. However, one of the biggest challenges for deploying FL in IoT networks is the unavailability of labeled data and dissimilarity of data features for training. In this paper, we propose a novel collaborative learning framework that leverages Transfer Learning (TL) to overcome these challenges. Particularly, we develop a novel collaborative learning approach that enables a target network with unlabeled data to effectively and quickly learn “knowledge” from a source network that possesses abundant labeled data. It is important that the state-of-the-art studies require the participated datasets of networks to have the same features, thus limiting the efficiency, flexibility as well as scalability of intrusion detection systems. However, our proposed framework can address these problems by exchanging the learning “knowledge” among various deep learning models, even when their datasets have different features. Extensive experiments on recent real-world cybersecurity datasets show that the proposed framework can improve more than 40% as compared to the state-of-the-art deep learning based approaches.

Development of Teaching Materials on Learning Economic Models to Improve Students’ Cognitive Achievement

The objectives of this research are to both produce products of teaching materials of Learning Economic Models and find their effects towards students’ cognitive achievement. Dick and Carey’s model was used for the concept of the development model. Formative tests were used to measure the effectiveness of teaching materials-and they were used to test one evaluation, small group evaluation, and field trial. The data collected was analyzed through mean, standard deviation, and z-test statistics. The research showed the products of teaching materials, with all being covered from Chapter 1 through Chapter 8 in order: 1) the theory of teaching and learning, 2) the basic concept learning models, 3) science-based learning models, 4) innovative learning models, 5) cooperative and collaborative learning models, 6) a model of problem-based learning, 7) contextual-based learning models, and 8) integrated learning models. The findings revealed that students with the teaching materials performed better than those without. The null hypothesis was tested at a 0.05 level of significance, indicating a significant difference between the cognitive achievement scores of those taught with the teaching materials and those taught without.