scholarly journals Harnessing Entropy via Predictive Analytics to Optimize Outcomes in the Pedagogical System: An Artificial Intelligence-Based Bayesian Networks Approach

2019 ◽  
Vol 9 (2) ◽  
pp. 158 ◽  
Author(s):  
Meng-Leong HOW ◽  
Wei Loong David HUNG
Keyword(s):  
Artificial Intelligence ◽  
Bayesian Networks ◽  
Conceptual Framework ◽  
Learning Outcomes ◽  
Predictive Analytics ◽  
Formative Assessments ◽  
Control Group ◽  
Worst Case ◽  
Educational Stakeholders ◽  
Computer Scientists

Educational stakeholders would be better informed if they could use their students’ formative assessments results and personal background attributes to predict the conditions for achieving favorable learning outcomes, and conversely, to gain awareness of the “at-risk” signals to prevent unfavorable or worst-case scenarios from happening. It remains, however, quite challenging to simulate predictive counterfactual scenarios and their outcomes, especially if the sample size is small, or if a baseline control group is unavailable. To overcome these constraints, the current paper proffers a Bayesian Networks approach to visualize the dynamics of the spread of “energy” within a pedagogical system, so that educational stakeholders, rather than computer scientists, can also harness entropy to work for them. The paper uses descriptive analytics to investigate “what has already happened?” in the collected data, followed by predictive analytics with controllable parameters to simulate outcomes of “what-if?” scenarios in the experimental Bayesian Network computational model to visualize how effects spread when interventions are applied. The conceptual framework and analytical procedures in this paper could be implemented using Bayesian Networks software, so that educational researchers and stakeholders would be able to use their own schools’ data and produce findings to inform and advance their practice.

scholarly journals Future-Ready Strategic Oversight of Multiple Artificial Superintelligence-Enabled Adaptive Learning Systems via Human-Centric Explainable AI-Empowered Predictive Optimizations of Educational Outcomes

2019 ◽  
Vol 3 (3) ◽  
pp. 46 ◽  
Author(s):  
HOW
Keyword(s):  
Artificial Intelligence ◽  
Adaptive Learning ◽  
Predictive Analytics ◽  
Learning Systems ◽  
Formative Assessments ◽  
Policy Makers ◽  
Educational Stakeholders ◽  
Summative Assessments ◽  
Adaptive Learning Systems ◽  
Network Software

Artificial intelligence-enabled adaptive learning systems (AI-ALS) have been increasingly utilized in education. Schools are usually afforded the freedom to deploy the AI-ALS that they prefer. However, even before artificial intelligence autonomously develops into artificial superintelligence in the future, it would be remiss to entirely leave the students to the AI-ALS without any independent oversight of the potential issues. For example, if the students score well in formative assessments within the AI-ALS but subsequently perform badly in paper-based post-tests, or if the relentless algorithm of a particular AI-ALS is suspected of causing undue stress for the students, they should be addressed by educational stakeholders. Policy makers and educational stakeholders should collaborate to analyze the data from multiple AI-ALS deployed in different schools to achieve strategic oversight. The current paper provides exemplars to illustrate how this future-ready strategic oversight could be implemented using an artificial intelligence-based Bayesian network software to analyze the data from five dissimilar AI-ALS, each deployed in a different school. Besides using descriptive analytics to reveal potential issues experienced by students within each AI-ALS, this human-centric AI-empowered approach also enables explainable predictive analytics of the students’ learning outcomes in paper-based summative assessments after training is completed in each AI-ALS.

scholarly journals Educational Stakeholders’ Independent Evaluation of an Artificial Intelligence-Enabled Adaptive Learning System Using Bayesian Network Predictive Simulations

2019 ◽  
Vol 9 (2) ◽  
pp. 110 ◽  
Author(s):  
Meng-Leong HOW ◽  
Wei Loong David HUNG
Keyword(s):  
Artificial Intelligence ◽  
Adaptive Learning ◽  
Large Scale ◽  
Small Sample Size ◽  
Small Sample ◽  
Learning System ◽  
Learning Needs ◽  
Educational Stakeholders ◽  
Independent Evaluation ◽  
Computer Scientists

Artificial intelligence-enabled adaptive learning systems (AI-ALS) are increasingly being deployed in education to enhance the learning needs of students. However, educational stakeholders are required by policy-makers to conduct an independent evaluation of the AI-ALS using a small sample size in a pilot study, before that AI-ALS can be approved for large-scale deployment. Beyond simply believing in the information provided by the AI-ALS supplier, there arises a need for educational stakeholders to independently understand the motif of the pedagogical characteristics that underlie the AI-ALS. Laudable efforts were made by researchers to engender frameworks for the evaluation of AI-ALS. Nevertheless, those highly technical techniques often require advanced mathematical knowledge or computer programming skills. There remains a dearth in the extant literature for a more intuitive way for educational stakeholders—rather than computer scientists—to carry out the independent evaluation of an AI-ALS to understand how it could provide opportunities to educe the problem-solving abilities of the students so that they can successfully learn the subject matter. This paper proffers an approach for educational stakeholders to employ Bayesian networks to simulate predictive hypothetical scenarios with controllable parameters to better inform them about the suitability of the AI-ALS for the students.

ENGARUH MODEL PEMBELAJARAN AKTIF COURSE REVIEW HORAY TERHADAP HASIL BELAJAR BIOLOGI SISWA KELAS VIII SMP NEGERI 10 BATAM

SIMBIOSA ◽  
2014 ◽  
Vol 3 (2) ◽  
Author(s):  
Ramses Ramses ◽  
Nurhaty Purnama Sari ◽  
Harni Lainy Br.Bakkara
Keyword(s):  
Active Learning ◽  
Learning Outcomes ◽  
Learning Model ◽  
T Test ◽  
Eighth Grade ◽  
Control Group ◽  
Homogeneity Test ◽  
Control Group Design ◽  
Eighth Grade Students ◽  
Biology Learning

This study aims to know the influence of active learning model Course Review Horay to biology learning outcomes at eighth grade students of SMP Negeri 10 Batam academic year 2013/2014. This research design is  randomized experiment using posttest only control-group design. The study population is all the eighth grade students of  SMP Negeri 10 Batam with reached population consist of 7 classes. The sampling technique using a simple random sampling. Samples were selected class VIII5 as control class and VIII8 as experiment class. The instrument  that use in this research is the form of the test. Requirement have been in the form of normality and homogeneity test, which showed that normal and homogeneous data. Technique of data analysis conducted by the t test. The result analysis of data using the t test showed the tvalue 3.01 and ttable is 2.00 (tvalue > ttable). The results showed that the active learning result model Course Review Horay give effect to increase student learning outcomes from the average of the experimental class 82,57 and control class 76,04. Thus, the hypothesis put forward acceptable significance level (α = 0.05). Thus, it can be concluded that the using of active learning model Course Review Horay influential on learning outcomes of biology at eighth grade students of SMP Negeri 10 Batam. Keywords: Course Review Horay, Biology Learning Outcomes.

The Using of Film Media to Analyze Intrinsic Element in Literature in High School

2019 ◽  
Vol 1 (2) ◽  
pp. 60
Author(s):  
Hendrick L ◽  
Martono Martono ◽  
Indri Astuti
Keyword(s):  
Data Analysis ◽  
Student Learning ◽  
Learning Outcomes ◽  
Literary Work ◽  
Student Learning Outcomes ◽  
T Test ◽  
Control Group ◽  
Homogeneity Test ◽  
Learning Material ◽  
Literary Works

This study examined the use of film media on Indonesian Language. The problem revealed was how is student learning outcomes, and what is the outcomes difference between learning to analyze the intrinsic elements of literary works using film media and using conventional learning approaches in class XI students of SMA N 1 Tumbang Titi. This type of research is experimental research. The design used was Post-test Only Control Group Design. Data analysis was done by normality test, homogeneity test, and t-test (Paired Simple t-Test). Data collection techniques in the form of tests. Based on the results of data analysis, it can be concluded that student learning outcomes analysis the intrinsic elements of literary works after being given conventional learning is 54.38 while student learning outcomes analyze the intrinsic elements of literary works after using film media is 71, 67. Besides, after analyzing the data statistically, the results show that there are significant differences between the learning outcomes of the material analyzing the intrinsic elements of literary work between those who use film media and conventional learning. Indonesian language learning material becomes the intrinsic elements of literature in class XI students of SMA N 1 Tumbang Titi using film media can also improve student learning outcomes and contribute to the scale of effectiveness of 32,64. Thus, learning with film media can be used by teachers in the field of learning Indonesian in analyzing intrinsic elements of literary works.Keywords: Utilization of Film Media, Intrinsic Elements of Literary Work

scholarly journals Predicting Student Performance Using Data Mining and Learning Analytics Techniques: A Systematic Literature Review

2020 ◽  
Vol 11 (1) ◽  
pp. 237
Author(s):  
Abdallah Namoun ◽  
Abdullah Alshanqiti
Keyword(s):  
Academic Success ◽  
Student Learning ◽  
Learning Outcomes ◽  
Student Performance ◽  
Student Outcomes ◽  
Predictive Analytics ◽  
Research Work ◽  
Supervised Machine Learning ◽  
Bibliographic Databases ◽  
Learning And Teaching

The prediction of student academic performance has drawn considerable attention in education. However, although the learning outcomes are believed to improve learning and teaching, prognosticating the attainment of student outcomes remains underexplored. A decade of research work conducted between 2010 and November 2020 was surveyed to present a fundamental understanding of the intelligent techniques used for the prediction of student performance, where academic success is strictly measured using student learning outcomes. The electronic bibliographic databases searched include ACM, IEEE Xplore, Google Scholar, Science Direct, Scopus, Springer, and Web of Science. Eventually, we synthesized and analyzed a total of 62 relevant papers with a focus on three perspectives, (1) the forms in which the learning outcomes are predicted, (2) the predictive analytics models developed to forecast student learning, and (3) the dominant factors impacting student outcomes. The best practices for conducting systematic literature reviews, e.g., PICO and PRISMA, were applied to synthesize and report the main results. The attainment of learning outcomes was measured mainly as performance class standings (i.e., ranks) and achievement scores (i.e., grades). Regression and supervised machine learning models were frequently employed to classify student performance. Finally, student online learning activities, term assessment grades, and student academic emotions were the most evident predictors of learning outcomes. We conclude the survey by highlighting some major research challenges and suggesting a summary of significant recommendations to motivate future works in this field.

scholarly journals Human-Centered Artificial Intelligence for Designing Accessible Cultural Heritage

2021 ◽  
Vol 11 (2) ◽  
pp. 870
Author(s):  
Galena Pisoni ◽  
Natalia Díaz-Rodríguez ◽  
Hannie Gijlers ◽  
Linda Tonolli
Keyword(s):  
Artificial Intelligence ◽  
Literature Review ◽  
Cultural Heritage ◽  
Conceptual Framework ◽  
Interaction Design ◽  
Participatory Design ◽  
Future Directions ◽  
Heritage Sites ◽  
Review Analysis

This paper reviews the literature concerning technology used for creating and delivering accessible museum and cultural heritage sites experiences. It highlights the importance of the delivery suited for everyone from different areas of expertise, namely interaction design, pedagogical and participatory design, and it presents how recent and future artificial intelligence (AI) developments can be used for this aim, i.e.,improving and widening online and in situ accessibility. From the literature review analysis, we articulate a conceptual framework that incorporates key elements that constitute museum and cultural heritage online experiences and how these elements are related to each other. Concrete opportunities for future directions empirical research for accessibility of cultural heritage contents are suggested and further discussed.

scholarly journals Responsible Urban Innovation with Local Government Artificial Intelligence (AI): A Conceptual Framework and Research Agenda

2021 ◽  
Vol 7 (1) ◽  
pp. 71
Author(s):  
Tan Yigitcanlar ◽  
Juan M. Corchado ◽  
Rashid Mehmood ◽  
Rita Yi Man Li ◽  
Karen Mossberger ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Local Government ◽  
Conceptual Framework ◽  
Research Agenda ◽  
Future Studies ◽  
Expert Team ◽  
Research Questions ◽  
Urban Problems ◽  
Technological Opportunities ◽  
Made In

The urbanization problems we face may be alleviated using innovative digital technology. However, employing these technologies entails the risk of creating new urban problems and/or intensifying the old ones instead of alleviating them. Hence, in a world with immense technological opportunities and at the same time enormous urbanization challenges, it is critical to adopt the principles of responsible urban innovation. These principles assure the delivery of the desired urban outcomes and futures. We contribute to the existing responsible urban innovation discourse by focusing on local government artificial intelligence (AI) systems, providing a literature and practice overview, and a conceptual framework. In this perspective paper, we advocate for the need for balancing the costs, benefits, risks and impacts of developing, adopting, deploying and managing local government AI systems in order to achieve responsible urban innovation. The statements made in this perspective paper are based on a thorough review of the literature, research, developments, trends and applications carefully selected and analyzed by an expert team of investigators. This study provides new insights, develops a conceptual framework and identifies prospective research questions by placing local government AI systems under the microscope through the lens of responsible urban innovation. The presented overview and framework, along with the identified issues and research agenda, offer scholars prospective lines of research and development; where the outcomes of these future studies will help urban policymakers, managers and planners to better understand the crucial role played by local government AI systems in ensuring the achievement of responsible outcomes.

scholarly journals Enhanced student perceptions of learning and performance using concept-point-recovery teaching sessions: a mixed-method approach

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hyun Jin Cho ◽  
Michael R. Melloch ◽  
Chantal Levesque-Bristol
Keyword(s):  
Academic Success ◽  
Active Learning ◽  
Learning Environment ◽  
Learning Outcomes ◽  
Student Perceptions ◽  
Psychological Needs ◽  
Basic Psychological Needs ◽  
Academic Learning ◽  
Control Group ◽  
The Impact

Abstract Background Active learning pedagogy has recently received a great deal of attention, and many universities have attempted to create student-centered learning environments to improve students’ academic success. The purpose of this study is to explore the impact of concept-point-recovery (CPR) teaching sessions as an active learning strategy on students’ perceptions of the learning environment, motivation, and academic learning outcomes in an electrical engineering course. To investigate the effectiveness of CPR sessions, students’ perceptions of learning and their performance were compared to those of students in a control classroom. Finally, students’ written comments on the course and instructor were explored in further analysis. Results The quantitative findings revealed that there was a significant change in students’ perceptions of learning after the CPR teaching sessions, and there was an increase in students’ perceptions and learning outcomes compared with those of the control group. In addition, the qualitative findings from students’ written feedback demonstrated that students felt that the instructor cared about students’ learning and success and that they had a positive learning environment. Conclusions CPR teaching sessions can be an alternative model for instructors to connect with students and create supportive environments to help students achieve academic success, which in turn promotes the satisfaction of students’ basic psychological needs and self-determined motivation. Therefore, increasing students’ engagement in their learning processes and making connections with students through CPR teaching sessions can facilitate improvements in students’ motivation and academic success. How this new active learning technique can be applied to higher education is discussed.

scholarly journals Comparison of the effectiveness of lecture instruction and virtual reality-based serious gaming instruction on the medical students’ learning outcome about approach to coma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Meysam Siyah Mansoory ◽  
Mohammad Rasool Khazaei ◽  
Seyyed Mohsen Azizi ◽  
Elham Niromand
Keyword(s):  
Virtual Reality ◽  
Medical Students ◽  
Learning Outcomes ◽  
Learning Outcome ◽  
Serious Game ◽  
Control Group ◽  
Serious Gaming ◽  
E Learning ◽  
The Mean ◽  
Lecture Instruction

Abstract Background New approaches to e-learning and the use of virtual reality technology and serious game in medical education are on the rise. Therefore, the purpose of this study was to compare the effectiveness of lecture method and virtual reality-based serious gaming (VRBSG) method on students learning outcomes about the approach to coma. Methods We adopted a randomized trial method for this study and selected 50 medical students dividing them into experimental and control groups. Students’ learning outcome was measured with a 10-item test. Serious game usability scale was used to evaluate the usability of the serious game. Descriptive and inferential statistics were used for data analysis by SPSS-22 software. Results Students’ familiarity with e-learning and VRBSG was low. The mean usability of a VRBSG was 126.78 ± 10.34 out of 150. The majority of students were eager to be instructed through VRBSG. The mean score of learning outcomes in the experimental group was significantly higher than the control group (t = − 2.457, P = 0.019). Conclusion Students’ learning outcomes in the VRBSG group in the test approach to coma were significantly better than the lecture group. The usability of the serious game instruction method was high. Taken together, instruction through VRBSG had an effective role in medical students’ learning.

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