Pub Date : 2024-04-08DOI: 10.37074/jalt.2024.7.1.32
{"title":"Evaluation of a research training workshop for academic staff in tertiary institutions: A Kirkpatrick model approach","authors":"","doi":"10.37074/jalt.2024.7.1.32","DOIUrl":"https://doi.org/10.37074/jalt.2024.7.1.32","url":null,"abstract":"","PeriodicalId":6298,"journal":{"name":"1","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140731069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-04DOI: 10.37074/jalt.2024.7.1.29
{"title":"A conceptual, strategic and implementation framework for the Scholarship of Learning and Teaching","authors":"","doi":"10.37074/jalt.2024.7.1.29","DOIUrl":"https://doi.org/10.37074/jalt.2024.7.1.29","url":null,"abstract":"","PeriodicalId":6298,"journal":{"name":"1","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140744097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-03DOI: 10.37074/jalt.2024.7.1.31
{"title":"Book review of Benedict du Boulay, Antonija Mitrovic, & Kalina Yacef (Eds., 2023). Handbook of artificial intelligence in education. Edward Elgar.","authors":"","doi":"10.37074/jalt.2024.7.1.31","DOIUrl":"https://doi.org/10.37074/jalt.2024.7.1.31","url":null,"abstract":"","PeriodicalId":6298,"journal":{"name":"1","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140748625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-02DOI: 10.37074/jalt.2024.7.1.30
{"title":"Book review of Lindgren, Simon (Ed., 2023). Handbook of critical studies of artificial intelligence. Edward Elgar.","authors":"","doi":"10.37074/jalt.2024.7.1.30","DOIUrl":"https://doi.org/10.37074/jalt.2024.7.1.30","url":null,"abstract":"","PeriodicalId":6298,"journal":{"name":"1","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140753185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-01DOI: 10.37074/jalt.2024.7.1.28
Bayode Ogunleye, K. I. Zakariyyah, Oluwaseun Ajao, Olakunle Olayinka, Hemlata Sharma
The higher education (HE) sector benefits every nation's economy and society at large. However, their contributions are challenged by advanced technologies like generative artificial intelligence (GenAI) tools. In this paper, we provide a comprehensive assessment of GenAI tools towards assessment and pedagogic practice and, subsequently, discuss the potential impacts. This study experimented using three assessment instruments from data science, data analytics, and construction management disciplines. Our findings are two-fold: first, the findings revealed that GenAI tools exhibit subject knowledge, problem-solving, analytical, critical thinking, and presentation skills and thus can limit learning when used unethically. Secondly, the design of the assessment of certain disciplines revealed the limitations of the GenAI tools. Based on our findings, we made recommendations on how AI tools can be utilised for teaching and learning in HE.
{"title":"Higher education assessment practice in the era of generative AI tools","authors":"Bayode Ogunleye, K. I. Zakariyyah, Oluwaseun Ajao, Olakunle Olayinka, Hemlata Sharma","doi":"10.37074/jalt.2024.7.1.28","DOIUrl":"https://doi.org/10.37074/jalt.2024.7.1.28","url":null,"abstract":"The higher education (HE) sector benefits every nation's economy and society at large. However, their contributions are challenged by advanced technologies like generative artificial intelligence (GenAI) tools. In this paper, we provide a comprehensive assessment of GenAI tools towards assessment and pedagogic practice and, subsequently, discuss the potential impacts. This study experimented using three assessment instruments from data science, data analytics, and construction management disciplines. Our findings are two-fold: first, the findings revealed that GenAI tools exhibit subject knowledge, problem-solving, analytical, critical thinking, and presentation skills and thus can limit learning when used unethically. Secondly, the design of the assessment of certain disciplines revealed the limitations of the GenAI tools. Based on our findings, we made recommendations on how AI tools can be utilised for teaching and learning in HE.","PeriodicalId":6298,"journal":{"name":"1","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140355183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recently, there has been a growing interest in distributed generation (DG) technologies, driven by various factors such as fuel price uncertainties, environmental constraints, and increasing power consumption along with transmission capacity shortages, in modern power systems. DG, which involves utilizing clean and renewable energy sources for power generation within the distribution system, has gained significant attention globally. Many developing countries, including Libya, are considering the adoption of DG technologies as part of their energy system expansion plans. Libya, located in North Africa and characterized by vast desert lands, has abundant solar radiation, making solar energy a promising and sustainable source of power. However, despite this energy potential, the southern part of Libya faces frequent power outages. In order to effectively maintain service quality, it is essential to conduct quantitative evaluation of wireless sensor networks. the evaluation of wireless sensor networks involves addressing the multiple attribute group decision-making (MAGDM) problem. To tackle the challenges of MAGDM, an extension of the classical EDAS (Evaluation based on Distance from Average Solution) method is proposed in this paper. The proposed method incorporates interval-valued intuitionistic fuzzy sets (IVIFSs), which provide a more flexible and comprehensive representation of uncertainty, to handle the complexities of MAGDM. The paper begins with a brief review of essential concepts related to IVIFSs. Then, the weights of attributes are determined using the CRITIC method. Subsequently, the IVIF-EDAS method is established by integrating the EDAS method with IVIFSs, and all the calculation procedures are described.
{"title":"Extended EDAS Analysis for Multi-Criteria Decision-Making Based on Distributed Generation (DG) Technologies System","authors":"","doi":"10.46632/jeae/3/1/5","DOIUrl":"https://doi.org/10.46632/jeae/3/1/5","url":null,"abstract":"Recently, there has been a growing interest in distributed generation (DG) technologies, driven by various factors such as fuel price uncertainties, environmental constraints, and increasing power consumption along with transmission capacity shortages, in modern power systems. DG, which involves utilizing clean and renewable energy sources for power generation within the distribution system, has gained significant attention globally. Many developing countries, including Libya, are considering the adoption of DG technologies as part of their energy system expansion plans. Libya, located in North Africa and characterized by vast desert lands, has abundant solar radiation, making solar energy a promising and sustainable source of power. However, despite this energy potential, the southern part of Libya faces frequent power outages. In order to effectively maintain service quality, it is essential to conduct quantitative evaluation of wireless sensor networks. the evaluation of wireless sensor networks involves addressing the multiple attribute group decision-making (MAGDM) problem. To tackle the challenges of MAGDM, an extension of the classical EDAS (Evaluation based on Distance from Average Solution) method is proposed in this paper. The proposed method incorporates interval-valued intuitionistic fuzzy sets (IVIFSs), which provide a more flexible and comprehensive representation of uncertainty, to handle the complexities of MAGDM. The paper begins with a brief review of essential concepts related to IVIFSs. Then, the weights of attributes are determined using the CRITIC method. Subsequently, the IVIF-EDAS method is established by integrating the EDAS method with IVIFSs, and all the calculation procedures are described.","PeriodicalId":6298,"journal":{"name":"1","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140213201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-19DOI: 10.37074/jalt.2024.7.1.26
{"title":"A content analysis of tweets on toxic doctoral supervision","authors":"","doi":"10.37074/jalt.2024.7.1.26","DOIUrl":"https://doi.org/10.37074/jalt.2024.7.1.26","url":null,"abstract":"","PeriodicalId":6298,"journal":{"name":"1","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140228520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.37074/jalt.2024.7.1.24
{"title":"Digital versus classroom discussions: Motivation and self-efficacy outcomes in speaking courses via Gather.town","authors":"","doi":"10.37074/jalt.2024.7.1.24","DOIUrl":"https://doi.org/10.37074/jalt.2024.7.1.24","url":null,"abstract":"","PeriodicalId":6298,"journal":{"name":"1","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140242182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-11DOI: 10.46632/10.46632/jame/3/1/2
The Electrostatic Precipitator (ESP) is a widely employed device in boilers to mitigate the release of particulate matter. This study proposes the design and fabrication of a similar device tailored for reducing emissions from automobiles, particularly targeting older versions of BS vehicles lacking dedicated emission control mechanisms. Despite the catalytic converters equipped in BS-6 vehicles, there exists a need for an efficient emission reduction solution for their predecessors. This research aims to analyse various ESP designs through Computational Fluid Dynamics (CFD) simulations using ANSYS software. The design optimization will be conducted based on fluid flow analysis, leading to the fabrication of the most optimal prototype. The final step involves testing the fabricated prototype to ensure compliance with Pollution Under Control (PUC) standards, contributing to environmental sustainability.
{"title":"Review on Enhancement of Electrostatic Precipitator in Automobiles","authors":"","doi":"10.46632/10.46632/jame/3/1/2","DOIUrl":"https://doi.org/10.46632/10.46632/jame/3/1/2","url":null,"abstract":"The Electrostatic Precipitator (ESP) is a widely employed device in boilers to mitigate the release of particulate matter. This study proposes the design and fabrication of a similar device tailored for reducing emissions from automobiles, particularly targeting older versions of BS vehicles lacking dedicated emission control mechanisms. Despite the catalytic converters equipped in BS-6 vehicles, there exists a need for an efficient emission reduction solution for their predecessors. This research aims to analyse various ESP designs through Computational Fluid Dynamics (CFD) simulations using ANSYS software. The design optimization will be conducted based on fluid flow analysis, leading to the fabrication of the most optimal prototype. The final step involves testing the fabricated prototype to ensure compliance with Pollution Under Control (PUC) standards, contributing to environmental sustainability.","PeriodicalId":6298,"journal":{"name":"1","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140252898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As for H13 die steel, it is distinguished by a high hardness and a unique surface characteristics that must be created during machining using non-standard methods. One of such non conventional manufacturing techniques involving the use of Electrical Discharge Machining (EDM) for machining complex or hard material parts. It indicates that EDM has progressed from a series of a tool and die process to an alternative micro-scale application machining process. The paper is aimed at elaborating mathematical models defining the link between the MRR and SR to measured input parameters (current, pulse-on time, pulse-off time, and Reference voltage) in hot work steel EDM. With a L9 orthogonal involving four variables at three levels were used. The values of the model quality factors analyzed by the ANOVA procedure show that the selected mathematical models describe the process performance within successfully studied range with high level of precision. To determine the optimal condition, Taguchi method was used to measure the performance impact of different process parameters and find out best mixing. Minitab V 21 software has been used for the analysis and explanations. A good agreement between experimental value and the predicted one was found.
H13 模具钢具有高硬度和独特的表面特征，必须在加工过程中使用非标准方法来制造。放电加工（EDM）就是其中一种非传统加工技术，用于加工复杂或硬质材料零件。这表明，放电加工已从一系列工具和模具加工工艺发展成为另一种微尺度应用加工工艺。本文旨在阐述热作钢电火花加工中 MRR 和 SR 与测量输入参数（电流、脉冲开启时间、脉冲关闭时间和参考电压）之间的数学模型。模型采用 L9 正交模型，涉及三个层次的四个变量。通过方差分析程序分析的模型质量因子值表明，所选数学模型在成功研究的范围内以较高的精度描述了工艺性能。为确定最佳条件，采用了田口方法来测量不同工艺参数对性能的影响，并找出最佳混合方式。Minitab V 21 软件用于分析和解释。实验值与预测值之间的吻合度很高。
{"title":"Parametric Study of Die Sinking EDM of H13 Steel using Taguchi Techniques","authors":"","doi":"10.46632/jame/3/1/4","DOIUrl":"https://doi.org/10.46632/jame/3/1/4","url":null,"abstract":"As for H13 die steel, it is distinguished by a high hardness and a unique surface characteristics that must be created during machining using non-standard methods. One of such non conventional manufacturing techniques involving the use of Electrical Discharge Machining (EDM) for machining complex or hard material parts. It indicates that EDM has progressed from a series of a tool and die process to an alternative micro-scale application machining process. The paper is aimed at elaborating mathematical models defining the link between the MRR and SR to measured input parameters (current, pulse-on time, pulse-off time, and Reference voltage) in hot work steel EDM. With a L9 orthogonal involving four variables at three levels were used. The values of the model quality factors analyzed by the ANOVA procedure show that the selected mathematical models describe the process performance within successfully studied range with high level of precision. To determine the optimal condition, Taguchi method was used to measure the performance impact of different process parameters and find out best mixing. Minitab V 21 software has been used for the analysis and explanations. A good agreement between experimental value and the predicted one was found.","PeriodicalId":6298,"journal":{"name":"1","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140253723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：