Rurality is rarely integrated into analyses of educational inequalities and this article presents an alternative perspective on rural–urban attainment and highlights the impact of rurality on educational outcomes. The traditional narrative of urban–rural educational disadvantage is that urban pupils do less well in the English exam system. Decontextualised data across different English exam performance measures demonstrate how rural pupils outperform their urban counterparts. Socioeconomic disadvantage (SED) has the most significant impact on attainment and this analysis explores the rural–urban attainment gap through this SED lens. An analysis of the Department for Education (DfE) data explores possible factors that might explain the emerging rural educational gap and presents an argument that rurality is another limiting factor that intersects with SED. This article demonstrates how rural underachievement in England has been hidden by the relative sizes and SED distribution of rural and urban populations.
这篇文章从另一个角度阐述了城乡教育成就，并强调了城乡教育对教育成果的影响。关于城乡教育劣势的传统说法是，城市学生在英语考试系统中成绩较差。不同英语考试成绩衡量标准的非背景化数据表明，农村学生的成绩要优于城市学生。社会经济劣势（SED）对学业成绩的影响最为显著，本分析从 SED 的角度探讨了城乡之间的学业成绩差距。对教育部（DfE）数据的分析探讨了可能解释新出现的农村教育差距的因素，并提出了一个论点，即农村是与社会经济弱势交织在一起的另一个限制因素。这篇文章说明了英格兰农村地区的成绩不佳是如何被城乡人口的相对规模和 SED 分布所掩盖的。
{"title":"The Grass Ceiling: Hidden Educational Barriers in Rural England","authors":"Luke Graham","doi":"10.3390/educsci14020165","DOIUrl":"https://doi.org/10.3390/educsci14020165","url":null,"abstract":"Rurality is rarely integrated into analyses of educational inequalities and this article presents an alternative perspective on rural–urban attainment and highlights the impact of rurality on educational outcomes. The traditional narrative of urban–rural educational disadvantage is that urban pupils do less well in the English exam system. Decontextualised data across different English exam performance measures demonstrate how rural pupils outperform their urban counterparts. Socioeconomic disadvantage (SED) has the most significant impact on attainment and this analysis explores the rural–urban attainment gap through this SED lens. An analysis of the Department for Education (DfE) data explores possible factors that might explain the emerging rural educational gap and presents an argument that rurality is another limiting factor that intersects with SED. This article demonstrates how rural underachievement in England has been hidden by the relative sizes and SED distribution of rural and urban populations.","PeriodicalId":502600,"journal":{"name":"Education Sciences","volume":"10 1-2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139863417","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}
Aistė Diržytė, V. Indrašienė, Violeta Jegeleviciene, O. Merfeldaitė, Romas Prakapas, Asta Railiene, Marina Gušauskienė
The links between different forms of teacher victimization and teachers’ life satisfaction are still under-researched. To highlight teacher victimization by various parties within the school environment and its associations with teachers’ life satisfaction, the Satisfaction with Life Scale, the Multidimensional Teacher Victimization Scale, and some additional measures were applied. The findings based on a Lithuanian sample (n = 1146) revealed that a significant portion of teachers have experienced victimization in various forms: 38.5% of teachers have been bullied by school staff, 33.9% have faced verbal victimization from students’ parents, and victimization by students affected 65.8% of teachers, with verbal and social victimization being the most common. An SEM analysis (χ2 = 355.787; Df = 33; CFI = 0.928; TLI = 0.902; NFI = 0.922; RMSEA = 0.092 [0.084–0.101]; SRMR = 0.0432) revealed that bullying by staff is not only detrimental in its own right but also relates positively to other forms of victimization, including verbal victimization by parents and multidimensional victimization by students, as teacher victimization by students and their parents mediated the relationship between teacher victimization by school staff and teacher life satisfaction. The findings suggest a complex problem within the school environment where different forms of victimization are interconnected and call for urgent attention and action from educational policymakers and school administrators to address and mitigate teacher victimization.
{"title":"Teacher Victimization by Students, Their Parents, and School Staff: Prevalence and Links with Teachers’ Life Satisfaction in a Lithuanian Sample","authors":"Aistė Diržytė, V. Indrašienė, Violeta Jegeleviciene, O. Merfeldaitė, Romas Prakapas, Asta Railiene, Marina Gušauskienė","doi":"10.3390/educsci14020163","DOIUrl":"https://doi.org/10.3390/educsci14020163","url":null,"abstract":"The links between different forms of teacher victimization and teachers’ life satisfaction are still under-researched. To highlight teacher victimization by various parties within the school environment and its associations with teachers’ life satisfaction, the Satisfaction with Life Scale, the Multidimensional Teacher Victimization Scale, and some additional measures were applied. The findings based on a Lithuanian sample (n = 1146) revealed that a significant portion of teachers have experienced victimization in various forms: 38.5% of teachers have been bullied by school staff, 33.9% have faced verbal victimization from students’ parents, and victimization by students affected 65.8% of teachers, with verbal and social victimization being the most common. An SEM analysis (χ2 = 355.787; Df = 33; CFI = 0.928; TLI = 0.902; NFI = 0.922; RMSEA = 0.092 [0.084–0.101]; SRMR = 0.0432) revealed that bullying by staff is not only detrimental in its own right but also relates positively to other forms of victimization, including verbal victimization by parents and multidimensional victimization by students, as teacher victimization by students and their parents mediated the relationship between teacher victimization by school staff and teacher life satisfaction. The findings suggest a complex problem within the school environment where different forms of victimization are interconnected and call for urgent attention and action from educational policymakers and school administrators to address and mitigate teacher victimization.","PeriodicalId":502600,"journal":{"name":"Education Sciences","volume":"20 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139804785","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}
Agnė Brandišauskienė, J. Česnavičienė, M. Bredikyte, Regina Sabaliauskiene
The early childhood curriculum is an integral part of the educational process, and many countries are looking at how to ensure its quality. With the decentralization of educational content in Lithuania, each Early Childhood Education and Care (ECEC) institution develops its own curriculum. In this case, the role of the head teacher at school and the leadership style they adopt become very important. Our study aims to investigate the expression of shared leadership in Lithuanian preschool education institutions and how it relates to the curriculum quality. An online survey was conducted in spring–autumn 2023. The sample was randomly selected from a list of kindergartens (N = 549) operating in Lithuania, and 133 kindergartens were selected. Of these, 79 (59.4%) institutions responded and agreed to participate. The research sample comprised 461 early childhood educators. The analysis of the survey data showed that distributed leadership can explain 61.3% of the quality of the curriculum. This means that if there is a higher degree of distributed leadership in the early childhood education community, the quality of the ECEC curriculum will likely be higher. ECEC leaders should pay attention to the individual scales of distributed leadership, collaboration, and cooperation.
{"title":"The Quality of Early Childhood Curricula and Distributed Leadership in Lithuanian ECEC Institutions","authors":"Agnė Brandišauskienė, J. Česnavičienė, M. Bredikyte, Regina Sabaliauskiene","doi":"10.3390/educsci14020166","DOIUrl":"https://doi.org/10.3390/educsci14020166","url":null,"abstract":"The early childhood curriculum is an integral part of the educational process, and many countries are looking at how to ensure its quality. With the decentralization of educational content in Lithuania, each Early Childhood Education and Care (ECEC) institution develops its own curriculum. In this case, the role of the head teacher at school and the leadership style they adopt become very important. Our study aims to investigate the expression of shared leadership in Lithuanian preschool education institutions and how it relates to the curriculum quality. An online survey was conducted in spring–autumn 2023. The sample was randomly selected from a list of kindergartens (N = 549) operating in Lithuania, and 133 kindergartens were selected. Of these, 79 (59.4%) institutions responded and agreed to participate. The research sample comprised 461 early childhood educators. The analysis of the survey data showed that distributed leadership can explain 61.3% of the quality of the curriculum. This means that if there is a higher degree of distributed leadership in the early childhood education community, the quality of the ECEC curriculum will likely be higher. ECEC leaders should pay attention to the individual scales of distributed leadership, collaboration, and cooperation.","PeriodicalId":502600,"journal":{"name":"Education Sciences","volume":"23 S1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139805594","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}
This paper aims to develop a new model of Project-Based Instructional Taxonomy (PBIT) that provides a tool of course design that facilitates Computational Thinking (CT) development as creative action in solving real-life problems. Theoretically, PBIT is built on an integrative framework bringing together with studies on CT education, creativity, Bloom’s Taxonomy, and Project-Based Instruction (PBI). This guides the course design to make alignment between diverse elements including education objectives, categories of CT, levels of learning ability, process of project facilitation, and methods of grading. A case will be discussed that focuses on a course Deep Learning and Technologies in AI bachelor program at Northeastern University (NEU) in China. It also shows how PBIT is applied in teaching practice that benefits students’ CT development. As the conclusion indicates, this paper has contributions to future research on creativity, PBI, CT, and AI education.
{"title":"Computational Thinking (CT) towards Creative Action: Developing a Project-Based Instructional Taxonomy (PBIT) in AI Education","authors":"Chunfang Zhou, Wei Zhang","doi":"10.3390/educsci14020134","DOIUrl":"https://doi.org/10.3390/educsci14020134","url":null,"abstract":"This paper aims to develop a new model of Project-Based Instructional Taxonomy (PBIT) that provides a tool of course design that facilitates Computational Thinking (CT) development as creative action in solving real-life problems. Theoretically, PBIT is built on an integrative framework bringing together with studies on CT education, creativity, Bloom’s Taxonomy, and Project-Based Instruction (PBI). This guides the course design to make alignment between diverse elements including education objectives, categories of CT, levels of learning ability, process of project facilitation, and methods of grading. A case will be discussed that focuses on a course Deep Learning and Technologies in AI bachelor program at Northeastern University (NEU) in China. It also shows how PBIT is applied in teaching practice that benefits students’ CT development. As the conclusion indicates, this paper has contributions to future research on creativity, PBI, CT, and AI education.","PeriodicalId":502600,"journal":{"name":"Education Sciences","volume":"13 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140489806","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}
The Gaokao, also known as China’s national college entrance exam, is a high-stakes exam for nearly all Chinese students. English has been one of the three most important subjects for a long time, and listening plays an important role in the Gaokao English test. However, relatively little research has been conducted on local versions of Gaokao’s English listening tests. This study analyzed the linguistic features and corresponding functional dimensions of the three different text types in the Gaokao’s listening test, investigating whether the papers used in three major regions of China were differentiated in terms of the co-occurrence patterns of lexicogrammatical features and dimensions of the transcripts. A corpus consisting of 170 sets of test papers (134,913 words) covering 31 provinces and cities from 2000 to 2022 was analyzed using a multidimensional analysis wherein six exclusive dimensions were extracted. The results showed that there were meaningful differences across short conversations, long conversations, and monologues with regard to the six dimensions’ scores, and regions further had significant differences in three dimensions: Syntactic and Clausal Complexity, Oral versus Literate Discourse, and Procedural Discourse, while Time Period was not associated with any differences. Implications for language teaching and assessment are discussed.
{"title":"A Multidimensional Analysis of a High-Stakes English Listening Test: A Corpus-Based Approach","authors":"Xuelian Tao, Vahid Aryadoust","doi":"10.3390/educsci14020137","DOIUrl":"https://doi.org/10.3390/educsci14020137","url":null,"abstract":"The Gaokao, also known as China’s national college entrance exam, is a high-stakes exam for nearly all Chinese students. English has been one of the three most important subjects for a long time, and listening plays an important role in the Gaokao English test. However, relatively little research has been conducted on local versions of Gaokao’s English listening tests. This study analyzed the linguistic features and corresponding functional dimensions of the three different text types in the Gaokao’s listening test, investigating whether the papers used in three major regions of China were differentiated in terms of the co-occurrence patterns of lexicogrammatical features and dimensions of the transcripts. A corpus consisting of 170 sets of test papers (134,913 words) covering 31 provinces and cities from 2000 to 2022 was analyzed using a multidimensional analysis wherein six exclusive dimensions were extracted. The results showed that there were meaningful differences across short conversations, long conversations, and monologues with regard to the six dimensions’ scores, and regions further had significant differences in three dimensions: Syntactic and Clausal Complexity, Oral versus Literate Discourse, and Procedural Discourse, while Time Period was not associated with any differences. Implications for language teaching and assessment are discussed.","PeriodicalId":502600,"journal":{"name":"Education Sciences","volume":"59 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140487166","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}
Grading student programming assignments is not an easy task. This task is even more challenging when talking about complex programming assignments at university graduate level. By complex assignments, we mean assignments where students have to program a complete application from scratch. For example, building a complete web application with a client and server side, whereby the application uses multiple threads that gather data from some external service (like the REST service, IoT sensors, etc.), processes these data and store them in some storage (e.g., a database), implements a custom protocol over a socket or something similar, implements their own REST/SOAP/GraphQL service, then sends or receives JMS/MQTT/WebSocket messages, etc. Such assignments give students an inside view of building real Internet applications. On the other hand, assignments like these take a long time to be tested and graded manually, e.g., up to 1 h per student. To speed up the assessment process, there are different automation possibilities that can check for the correctness of some application parts without endangering the grading quality. In this study, different possibilities of automation are described that have been improved over several years. This process takes advantage of unit testing, bash scripting, and other methods. The main goal of this study is to define an assessment process that can be used to grade complex programming assignments, with concrete examples of what and how to automate. This process involves assignment preparation for automation, plagiarism (i.e., better said similarity) detection, performing an automatic check of the correctness of each programming assignment, conducting an analysis of the obtained data, the awarding of points (grading) for each programming assignment, and other such activities. We also discuss what the downsides of automation are and why it is not possible to completely automate the grading process.
{"title":"Assessment Automation of Complex Student Programming Assignments","authors":"Matija Novak, D. Kermek","doi":"10.3390/educsci14010054","DOIUrl":"https://doi.org/10.3390/educsci14010054","url":null,"abstract":"Grading student programming assignments is not an easy task. This task is even more challenging when talking about complex programming assignments at university graduate level. By complex assignments, we mean assignments where students have to program a complete application from scratch. For example, building a complete web application with a client and server side, whereby the application uses multiple threads that gather data from some external service (like the REST service, IoT sensors, etc.), processes these data and store them in some storage (e.g., a database), implements a custom protocol over a socket or something similar, implements their own REST/SOAP/GraphQL service, then sends or receives JMS/MQTT/WebSocket messages, etc. Such assignments give students an inside view of building real Internet applications. On the other hand, assignments like these take a long time to be tested and graded manually, e.g., up to 1 h per student. To speed up the assessment process, there are different automation possibilities that can check for the correctness of some application parts without endangering the grading quality. In this study, different possibilities of automation are described that have been improved over several years. This process takes advantage of unit testing, bash scripting, and other methods. The main goal of this study is to define an assessment process that can be used to grade complex programming assignments, with concrete examples of what and how to automate. This process involves assignment preparation for automation, plagiarism (i.e., better said similarity) detection, performing an automatic check of the correctness of each programming assignment, conducting an analysis of the obtained data, the awarding of points (grading) for each programming assignment, and other such activities. We also discuss what the downsides of automation are and why it is not possible to completely automate the grading process.","PeriodicalId":502600,"journal":{"name":"Education Sciences","volume":"78 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139125067","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}
Dawn M. Pilotti, Kristin E. Harbour, Bridget T. Miller, Emma K. Larkin
Professional learning communities (PLCs) support the growth of educators to improve learning outcomes for all students. Guided by social constructivist and social cognitive theories, this longitudinal participatory action research study explored the implementation of an interdepartmental PLC across Hord’s five dimensions of a successful PLC—supportive and shared leadership, shared beliefs values and vision, collective learning and its application, shared personal practice, and supportive conditions. Additionally, this study explored how engaging with an interdepartmental PLC influenced participants’ collective efficacy. During the PLC, the collective expertise of mathematics teachers, administrators, and additional educational specialists (such as occupational therapists and speech and language pathologists) (n = 13) were leveraged to develop strategies for the improvement of mathematical problem solving among elementary and middle school students with disabilities. Our findings indicate statistically significant increases in the five dimensions of the PLC over time, with qualitative evidence supporting the PLC’s effectiveness. However, our findings revealed no significant increase in participants’ overall collective efficacy, a group’s shared belief that together they can achieve a desired result. Implications for practice and research are discussed.
{"title":"Creating Cohesion and Collaboration in Mathematics Classrooms: Implementing Interdepartmental Professional Learning Communities to Support Students with Disabilities","authors":"Dawn M. Pilotti, Kristin E. Harbour, Bridget T. Miller, Emma K. Larkin","doi":"10.3390/educsci14010050","DOIUrl":"https://doi.org/10.3390/educsci14010050","url":null,"abstract":"Professional learning communities (PLCs) support the growth of educators to improve learning outcomes for all students. Guided by social constructivist and social cognitive theories, this longitudinal participatory action research study explored the implementation of an interdepartmental PLC across Hord’s five dimensions of a successful PLC—supportive and shared leadership, shared beliefs values and vision, collective learning and its application, shared personal practice, and supportive conditions. Additionally, this study explored how engaging with an interdepartmental PLC influenced participants’ collective efficacy. During the PLC, the collective expertise of mathematics teachers, administrators, and additional educational specialists (such as occupational therapists and speech and language pathologists) (n = 13) were leveraged to develop strategies for the improvement of mathematical problem solving among elementary and middle school students with disabilities. Our findings indicate statistically significant increases in the five dimensions of the PLC over time, with qualitative evidence supporting the PLC’s effectiveness. However, our findings revealed no significant increase in participants’ overall collective efficacy, a group’s shared belief that together they can achieve a desired result. Implications for practice and research are discussed.","PeriodicalId":502600,"journal":{"name":"Education Sciences","volume":"31 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139131230","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}
Roberto López-Chila, Joe Llerena-Izquierdo, Nicolás Sumba-Nacipucha, Jorge Cueva-Estrada
Since its origin in the 1950s, artificial intelligence (AI) has evolved from technological to educational applications. AI is emerging as an essential tool in education. Its integration into education promises the personalization and the globalization of learning. Despite its potential, it is crucial to consider its ethical challenges and uses. This bibliometric study sought to understand the current state of AI in higher education in order to provide a basis for future research. A bibliometric analysis was conducted between 2017 and 2023, using the Scopus database. The query was performed on 23 October 2023 and focused on titles, keywords, and abstracts. A total of 870 articles were found, and their metadata were analyzed after removing incorrect data. VOSviewer software was used to visualize the similarities, and the publications were studied by country, authors, and collaborations. A steady growth in AI studies in higher education was found, highlighting areas such as computer science and social sciences. China and the United States led in production and citations. Keywords such as “artificial intelligence”, “chatgpt”, and “machine learning” indicated trends and areas of interest.
{"title":"Artificial Intelligence in Higher Education: An Analysis of Existing Bibliometrics","authors":"Roberto López-Chila, Joe Llerena-Izquierdo, Nicolás Sumba-Nacipucha, Jorge Cueva-Estrada","doi":"10.3390/educsci14010047","DOIUrl":"https://doi.org/10.3390/educsci14010047","url":null,"abstract":"Since its origin in the 1950s, artificial intelligence (AI) has evolved from technological to educational applications. AI is emerging as an essential tool in education. Its integration into education promises the personalization and the globalization of learning. Despite its potential, it is crucial to consider its ethical challenges and uses. This bibliometric study sought to understand the current state of AI in higher education in order to provide a basis for future research. A bibliometric analysis was conducted between 2017 and 2023, using the Scopus database. The query was performed on 23 October 2023 and focused on titles, keywords, and abstracts. A total of 870 articles were found, and their metadata were analyzed after removing incorrect data. VOSviewer software was used to visualize the similarities, and the publications were studied by country, authors, and collaborations. A steady growth in AI studies in higher education was found, highlighting areas such as computer science and social sciences. China and the United States led in production and citations. Keywords such as “artificial intelligence”, “chatgpt”, and “machine learning” indicated trends and areas of interest.","PeriodicalId":502600,"journal":{"name":"Education Sciences","volume":" 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139136276","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}
This work presents the process of validation of the community of inquiry (CoI) survey in its Italian version. For over two decades, the CoI framework has been used to conceptualize online higher-order teaching/learning experiences as processes of inquiry in which participants collaborate in discourse and critical reflection to cocreate knowledge and achieve meaningful learning. The CoI is hinged on the mutual interaction of three dimensions named presences: teaching presence, social presence, and cognitive presence. The official survey to detect the level of presence perceived by learners has been predominantly conducted in English. In recent years, a number of scholars have deemed that its original format suits at least a B2 level of English proficiency, and several translations in other languages have been validated. Accordingly, the validation of the Italian version aims to improve the accuracy of the CoI questionnaire conducted among native Italian learners (n = 234). Analyses show satisfactory outputs in terms of validity and reliability of the 34 Likert-scale items, whilst adaptations to other languages open new perspectives grounded on cultural variables.
这项工作介绍了意大利语版本的探究社区（CoI）调查的验证过程。二十多年来，CoI 框架一直被用于将在线高阶教学/学习体验概念化为探究过程，在这一过程中，参与者通过合作讨论和批判性反思来共同创造知识并实现有意义的学习。CoI 以三个维度的相互影响为基础，这三个维度分别是：教学临场感、社会临场感和认知临场感。为检测学习者感知的临场水平而进行的官方调查主要以英语进行。近年来，一些学者认为其原始格式至少适合 B2 水平的英语水平，而且其他语言的一些译本也得到了验证。因此，对意大利语版本进行验证的目的是提高在意大利母语学习者（n = 234）中进行的 CoI 问卷调查的准确性。分析表明，34 个李克特量表项目的有效性和可靠性令人满意，而根据文化变量对其他语言的改编则开辟了新的视角。
{"title":"Validation of the Italian Version of the Community of Inquiry Survey","authors":"Salvatore Nizzolino, A. Canals, Marco Temperini","doi":"10.3390/educsci13121200","DOIUrl":"https://doi.org/10.3390/educsci13121200","url":null,"abstract":"This work presents the process of validation of the community of inquiry (CoI) survey in its Italian version. For over two decades, the CoI framework has been used to conceptualize online higher-order teaching/learning experiences as processes of inquiry in which participants collaborate in discourse and critical reflection to cocreate knowledge and achieve meaningful learning. The CoI is hinged on the mutual interaction of three dimensions named presences: teaching presence, social presence, and cognitive presence. The official survey to detect the level of presence perceived by learners has been predominantly conducted in English. In recent years, a number of scholars have deemed that its original format suits at least a B2 level of English proficiency, and several translations in other languages have been validated. Accordingly, the validation of the Italian version aims to improve the accuracy of the CoI questionnaire conducted among native Italian learners (n = 234). Analyses show satisfactory outputs in terms of validity and reliability of the 34 Likert-scale items, whilst adaptations to other languages open new perspectives grounded on cultural variables.","PeriodicalId":502600,"journal":{"name":"Education Sciences","volume":"16 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139214326","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}
How does a child learn to read a map? In 2007, the authors of an article in the Journal of Geography proposed a tentative list of eight “modes of spatial reasoning” that children may use to organize their perceptions of information on a map. As an update, this article has short descriptions of these modes, brief reviews of research since 2007, and some suggestions of topics for future investigation. This article includes a brief look at some implications for teaching math and reading, followed by an extended report about a classroom activity that underscores the main point about the parallel perception and processing of different kinds of spatial information. A technical appendix has a more detailed summary of the process used to identify and classify the modes of spatial reasoning.
儿童如何学习阅读地图？2007 年，《地理学杂志》（Journal of Geography）上的一篇文章的作者提出了八种 "空间推理模式 "的初步清单，儿童可能会使用这些模式来组织他们对地图上信息的感知。作为更新，本文对这些模式进行了简短描述，对 2007 年以来的研究进行了简要回顾，并对未来研究的主题提出了一些建议。本文还简要介绍了对数学和阅读教学的一些启示，随后是一篇关于课堂活动的扩展报告，强调了平行感知和处理不同类型空间信息的要点。技术附录对空间推理模式的识别和分类过程进行了更详细的总结。
{"title":"Brain Science and Geographic Thinking: A Review and Research Agenda for K-3 Geography","authors":"Phil Gersmehl","doi":"10.3390/educsci13121199","DOIUrl":"https://doi.org/10.3390/educsci13121199","url":null,"abstract":"How does a child learn to read a map? In 2007, the authors of an article in the Journal of Geography proposed a tentative list of eight “modes of spatial reasoning” that children may use to organize their perceptions of information on a map. As an update, this article has short descriptions of these modes, brief reviews of research since 2007, and some suggestions of topics for future investigation. This article includes a brief look at some implications for teaching math and reading, followed by an extended report about a classroom activity that underscores the main point about the parallel perception and processing of different kinds of spatial information. A technical appendix has a more detailed summary of the process used to identify and classify the modes of spatial reasoning.","PeriodicalId":502600,"journal":{"name":"Education Sciences","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139211373","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}
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