With the increasing demand for programming skills comes a trend towards more online programming courses and assessments. While this allows educators to teach larger groups of students, it also opens the door to dishonest student behaviour, such as copying code from other students. When teachers use assignments where all students write code for the same problem, source code similarity tools can help to combat plagiarism. Unfortunately, teachers often do not use these tools to prevent such behaviour. In response to this challenge, we have developed a new source code plagiarism detection tool named Dolos. Dolos is open-source, supports a wide range of programming languages, and is designed to be user-friendly. It enables teachers to detect, prove and prevent plagiarism in programming courses by using fast algorithms and powerful visualisations. We present further enhancements to Dolos and discuss how it can be integrated into modern computing education courses to meet the challenges of online learning and assessment. By lowering the barriers for teachers to detect, prove and prevent plagiarism in programming courses, Dolos can help protect academic integrity and ensure that students earn their grades honestly.
{"title":"Dolos 2.0: Towards Seamless Source Code Plagiarism Detection in Online Learning Environments","authors":"Rien Maertens, P. Dawyndt, Bart Mesuere","doi":"10.1145/3587103.3594166","DOIUrl":"https://doi.org/10.1145/3587103.3594166","url":null,"abstract":"With the increasing demand for programming skills comes a trend towards more online programming courses and assessments. While this allows educators to teach larger groups of students, it also opens the door to dishonest student behaviour, such as copying code from other students. When teachers use assignments where all students write code for the same problem, source code similarity tools can help to combat plagiarism. Unfortunately, teachers often do not use these tools to prevent such behaviour. In response to this challenge, we have developed a new source code plagiarism detection tool named Dolos. Dolos is open-source, supports a wide range of programming languages, and is designed to be user-friendly. It enables teachers to detect, prove and prevent plagiarism in programming courses by using fast algorithms and powerful visualisations. We present further enhancements to Dolos and discuss how it can be integrated into modern computing education courses to meet the challenges of online learning and assessment. By lowering the barriers for teachers to detect, prove and prevent plagiarism in programming courses, Dolos can help protect academic integrity and ensure that students earn their grades honestly.","PeriodicalId":366365,"journal":{"name":"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123105167","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}
A common instructional approach to many CS and engineering classes involves designing a new software system, by providing real-world, open-ended, client-driven, team-based problems, most known as Model-Eliciting Activities (MEAs). A significant challenge imposed by this approach comes from accurately and consistently assessing student work where more than one solution can be correct. Therefore, timely feedback is pivotal for student success. Such feedback is fundamental in supporting grading consistency and efficiency for graders, but importantly to scaffold student understanding for student teams working on complex, ill-defined, real-world problems. This poster presents the next step in a two-phase evaluation (the first being a usability test) of a new grading and annotation tool for online technical reports, called e2Logos (evaluating electronic logos). We propose a plan for evaluating the educational impact of e2Logos in the context of an upper-level CS elective course on Human-Computer Interaction (HCI). The poster will also include a brief presentation of e2Logos, which aims to fill a gap in assessing and grading the rich type of student work submitted in project-based learning (PBL) courses employing MEAs.
{"title":"Assessing the Impact of Feedback on Student Learning Using e2Logos: A Novel Grading Tool for Online Student Reports","authors":"P. Apostolellis, L. Wheeler, Lynn Mandeltort","doi":"10.1145/3587103.3594183","DOIUrl":"https://doi.org/10.1145/3587103.3594183","url":null,"abstract":"A common instructional approach to many CS and engineering classes involves designing a new software system, by providing real-world, open-ended, client-driven, team-based problems, most known as Model-Eliciting Activities (MEAs). A significant challenge imposed by this approach comes from accurately and consistently assessing student work where more than one solution can be correct. Therefore, timely feedback is pivotal for student success. Such feedback is fundamental in supporting grading consistency and efficiency for graders, but importantly to scaffold student understanding for student teams working on complex, ill-defined, real-world problems. This poster presents the next step in a two-phase evaluation (the first being a usability test) of a new grading and annotation tool for online technical reports, called e2Logos (evaluating electronic logos). We propose a plan for evaluating the educational impact of e2Logos in the context of an upper-level CS elective course on Human-Computer Interaction (HCI). The poster will also include a brief presentation of e2Logos, which aims to fill a gap in assessing and grading the rich type of student work submitted in project-based learning (PBL) courses employing MEAs.","PeriodicalId":366365,"journal":{"name":"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131200090","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}
Mechanical engineering (ME) students have specific domain knowledge in developing physical systems, such as machines, vehicles and production equipment. Nevertheless, the strong demands of utilizing artificial intelligence (AI) for physical systems to become a cyber-physical system (CPS) is now a commonplace of modern physical systems. Hence, it is necessary to cultivate greater AI design and programming capabilities in ME students. In this poster, the "Intelligent Systems: Theory and Practice" course (ME5061 in ME, National Taiwan University) for senior undergraduate/ graduate students) is presented. This course has been offered once in the spring semester of 2022, and 34 students participated in this course.
{"title":"Teaching Artificial Intelligence in Mechanical Engineering to Cultivate Cyber-physical System Talents","authors":"C. Kuo, Phuc Thanh-Thien Nguyen, Shih-Lin Wu","doi":"10.1145/3587103.3594193","DOIUrl":"https://doi.org/10.1145/3587103.3594193","url":null,"abstract":"Mechanical engineering (ME) students have specific domain knowledge in developing physical systems, such as machines, vehicles and production equipment. Nevertheless, the strong demands of utilizing artificial intelligence (AI) for physical systems to become a cyber-physical system (CPS) is now a commonplace of modern physical systems. Hence, it is necessary to cultivate greater AI design and programming capabilities in ME students. In this poster, the \"Intelligent Systems: Theory and Practice\" course (ME5061 in ME, National Taiwan University) for senior undergraduate/ graduate students) is presented. This course has been offered once in the spring semester of 2022, and 34 students participated in this course.","PeriodicalId":366365,"journal":{"name":"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134442465","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 aim of this doctoral thesis is to develop a visualisation model to improve the learning process of syntax-driven translation, for which a software tool is being created. This program, aimed both to teachers and students, will allow to load a grammar and generate the visualization with the provided input. A generation API is currently available for teachers to annotate their specifications and generate the visualization, although the goal in the future is to do this process through an automatic annotation of the specifications.
{"title":"Application of Software Visualization for Syntax-directed Translation Learning","authors":"Ángel Francisco Sánchez-Granados","doi":"10.1145/3587103.3594136","DOIUrl":"https://doi.org/10.1145/3587103.3594136","url":null,"abstract":"The aim of this doctoral thesis is to develop a visualisation model to improve the learning process of syntax-driven translation, for which a software tool is being created. This program, aimed both to teachers and students, will allow to load a grammar and generate the visualization with the provided input. A generation API is currently available for teachers to annotate their specifications and generate the visualization, although the goal in the future is to do this process through an automatic annotation of the specifications.","PeriodicalId":366365,"journal":{"name":"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128771455","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 use of microcontroller boards such as the Calliope Mini and BBC micro:bit is becoming increasingly popular in schools due to their versatility and affordability. This doctoral research aims to investigate the effectiveness and motivational potential of using microcontroller boards to introduce basic programming concepts to upper primary and lower secondary school students using Python. The primary focus is on the multi-context nature of microcontroller boards, exploring whether teaching programming concepts in different contexts, such as music, video games, and autonomous driving, can motivate a broader population of students compared to a single-context curriculum, such as Turtle Graphics or autonomous mobile robots. The research employs an educational design-based research approach. In the first cycle, a curriculum consisting of six lessons was developed and piloted in the context of gifted pull-out activities. The preliminary exploratory pilot study provides qualitative findings on students' responses to the curriculum, and algorithmic thinking gains were measured using a pre- and post-test. The results suggest that the curriculum has the potential to be an effective and engaging way to introduce basic programming concepts and that further research is needed to confirm these findings for larger populations. In the next educational design-based research cycle we plan to refine our measurement instruments and study design.
{"title":"Multi-context Physical Computing","authors":"Alexandra Maximova","doi":"10.1145/3587103.3594147","DOIUrl":"https://doi.org/10.1145/3587103.3594147","url":null,"abstract":"The use of microcontroller boards such as the Calliope Mini and BBC micro:bit is becoming increasingly popular in schools due to their versatility and affordability. This doctoral research aims to investigate the effectiveness and motivational potential of using microcontroller boards to introduce basic programming concepts to upper primary and lower secondary school students using Python. The primary focus is on the multi-context nature of microcontroller boards, exploring whether teaching programming concepts in different contexts, such as music, video games, and autonomous driving, can motivate a broader population of students compared to a single-context curriculum, such as Turtle Graphics or autonomous mobile robots. The research employs an educational design-based research approach. In the first cycle, a curriculum consisting of six lessons was developed and piloted in the context of gifted pull-out activities. The preliminary exploratory pilot study provides qualitative findings on students' responses to the curriculum, and algorithmic thinking gains were measured using a pre- and post-test. The results suggest that the curriculum has the potential to be an effective and engaging way to introduce basic programming concepts and that further research is needed to confirm these findings for larger populations. In the next educational design-based research cycle we plan to refine our measurement instruments and study design.","PeriodicalId":366365,"journal":{"name":"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133584342","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}
Monica Mcgill, S. Heckman, Christos Chytas, Lien Diaz, Michael Liut, V. Kazakova, I. T. Sanusi, Selina Marianna Shah, Claudia Szabo
To investigate and identify promising practices in equitable K-12 computer science (CS) education, the capacity for education researchers to conduct this research must be rapidly built globally. Simultaneously, concerns have arisen over the last few years about the quality of research that is being conducted and the lack of equity-focused research. In this working group, we will tackle the research question: In what ways can previous research standards inform high-quality, equity-focused K-12 CS education research? We will use existing research and various standards bodies (e.g., European Educational Research Association, Australian Education Research Organisation, CONSORT, American Psychological Association) to synthesize key features in the context of equity-focused K-12 CS education research. We will then vet these attributes with experts who can provide feedback and refine our recommendations and guidelines. Our working group will select the experts using a strata reflecting a diversity of backgrounds and experiences to support our focus on student populations that have been historically marginalized in computing (e.g., low-income students, rural students, girls, students with disabilities). Our recommendations will directly impact future equitable computing education research by providing guidance on conducting high-quality research such that the findings can be aggregated and impact future policy with evidence-based results. While we recognize that different countries and regions may yield differing answers to this question, our recommendations will be robust enough that researchers in each country or region may choose to use those most appropriate to their context.
{"title":"Building Recommendations for Conducting Equity-Focused, High Quality K-12 Computer Science Education Research","authors":"Monica Mcgill, S. Heckman, Christos Chytas, Lien Diaz, Michael Liut, V. Kazakova, I. T. Sanusi, Selina Marianna Shah, Claudia Szabo","doi":"10.1145/3587103.3594207","DOIUrl":"https://doi.org/10.1145/3587103.3594207","url":null,"abstract":"To investigate and identify promising practices in equitable K-12 computer science (CS) education, the capacity for education researchers to conduct this research must be rapidly built globally. Simultaneously, concerns have arisen over the last few years about the quality of research that is being conducted and the lack of equity-focused research. In this working group, we will tackle the research question: In what ways can previous research standards inform high-quality, equity-focused K-12 CS education research? We will use existing research and various standards bodies (e.g., European Educational Research Association, Australian Education Research Organisation, CONSORT, American Psychological Association) to synthesize key features in the context of equity-focused K-12 CS education research. We will then vet these attributes with experts who can provide feedback and refine our recommendations and guidelines. Our working group will select the experts using a strata reflecting a diversity of backgrounds and experiences to support our focus on student populations that have been historically marginalized in computing (e.g., low-income students, rural students, girls, students with disabilities). Our recommendations will directly impact future equitable computing education research by providing guidance on conducting high-quality research such that the findings can be aggregated and impact future policy with evidence-based results. While we recognize that different countries and regions may yield differing answers to this question, our recommendations will be robust enough that researchers in each country or region may choose to use those most appropriate to their context.","PeriodicalId":366365,"journal":{"name":"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134081246","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}
In this study, we developed an instructional module consisting of four units to help high school students understand the 4V concepts of big data by exploring air pollution. The instructional module enabled students to explore air quality data on specific websites, and asked students to create a "calendar heat map" using open dataset. We taught the module in a high school class and the results demonstrated that students gained knowledge about big data, and became more aware of the impact of air pollution in their lives.
{"title":"Teaching Big Data Concepts through Air Pollution Data: A High School Instructional Module","authors":"Jui-Ting Chen, Chiu-Fan Hu, Cheng-Chih Wu","doi":"10.1145/3587103.3594194","DOIUrl":"https://doi.org/10.1145/3587103.3594194","url":null,"abstract":"In this study, we developed an instructional module consisting of four units to help high school students understand the 4V concepts of big data by exploring air pollution. The instructional module enabled students to explore air quality data on specific websites, and asked students to create a \"calendar heat map\" using open dataset. We taught the module in a high school class and the results demonstrated that students gained knowledge about big data, and became more aware of the impact of air pollution in their lives.","PeriodicalId":366365,"journal":{"name":"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2","volume":"330 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130918079","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}
J. Prather, Paul Denny, Juho Leinonen, Brett A. Becker, Ibrahim Albluwi, M. Caspersen, Michelle Craig, H. Keuning, Natalie Kiesler, Tobias Kohn, Andrew Luxton-Reilly, S. Macneil, Andrew Petersen, Raymond Pettit, B. Reeves, Jaromír Šavelka
The recent advent of highly accurate and scalable large language models (LLMs) has taken the world by storm. From art to essays to computer code, LLMs are producing novel content that until recently was thought only humans could produce. Recent work in computing education has sought to understand the capabilities of LLMs for solving tasks such as writing code, explaining code, creating novel coding assignments, interpreting programming error messages, and more. However, these technologies continue to evolve at an astonishing rate leaving educators little time to adapt. This working group seeks to document the state-of-the-art for code generation LLMs, detail current opportunities and challenges related to their use, and present actionable approaches to integrating them into computing curricula.
{"title":"Transformed by Transformers: Navigating the AI Coding Revolution for Computing Education: An ITiCSE Working Group Conducted by Humans","authors":"J. Prather, Paul Denny, Juho Leinonen, Brett A. Becker, Ibrahim Albluwi, M. Caspersen, Michelle Craig, H. Keuning, Natalie Kiesler, Tobias Kohn, Andrew Luxton-Reilly, S. Macneil, Andrew Petersen, Raymond Pettit, B. Reeves, Jaromír Šavelka","doi":"10.1145/3587103.3594206","DOIUrl":"https://doi.org/10.1145/3587103.3594206","url":null,"abstract":"The recent advent of highly accurate and scalable large language models (LLMs) has taken the world by storm. From art to essays to computer code, LLMs are producing novel content that until recently was thought only humans could produce. Recent work in computing education has sought to understand the capabilities of LLMs for solving tasks such as writing code, explaining code, creating novel coding assignments, interpreting programming error messages, and more. However, these technologies continue to evolve at an astonishing rate leaving educators little time to adapt. This working group seeks to document the state-of-the-art for code generation LLMs, detail current opportunities and challenges related to their use, and present actionable approaches to integrating them into computing curricula.","PeriodicalId":366365,"journal":{"name":"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125115786","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}
Computer science education in the Czech Republic's primary school curriculum (ISCED 1) is now, similar to other countries, undergoing a transformation to respond current needs. This includes principles of how the Internet functions. Little is known about how prepared novice primary school teachers are for teaching this topic. Here, we have taken one step in addressing this issue by examining what preconceptions novice Czech primary school teachers have about how the Internet functions (N = 62; semi-structured interviews). Data are analysed using thematic and frequency analyses. Preliminary results suggest that teachers have many misconceptions about how the Internet works.
{"title":"What Does the Internet Look Like? Novice Primary School Teachers' Preconceptions about the Internet: Preliminary Results","authors":"A. Drobná, Anna Yaghobová, C. Brom","doi":"10.1145/3587103.3594205","DOIUrl":"https://doi.org/10.1145/3587103.3594205","url":null,"abstract":"Computer science education in the Czech Republic's primary school curriculum (ISCED 1) is now, similar to other countries, undergoing a transformation to respond current needs. This includes principles of how the Internet functions. Little is known about how prepared novice primary school teachers are for teaching this topic. Here, we have taken one step in addressing this issue by examining what preconceptions novice Czech primary school teachers have about how the Internet functions (N = 62; semi-structured interviews). Data are analysed using thematic and frequency analyses. Preliminary results suggest that teachers have many misconceptions about how the Internet works.","PeriodicalId":366365,"journal":{"name":"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133315683","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}
Angela Zavaleta Bernuy, Naaz Sibia, Pan Chen, Chloe Huang, Andrew Petersen, J. J. Williams, Michael Liut
Generating self-explanations has been identified as a successful strategy in helping learners engage with course content and organize what they learn in a structured format. While typing an explanation may allow more structure and formality, explaining by voice can be more natural and help free cognitive resources to focus on learning goals and understanding concepts. As we investigated the effects and students' perceptions of using voice or text to self-explain new course concepts, we failed to find a tool that would meet our needs. We present our work in designing and developing VoiceEx, a submission courseware that allows text and voice input to collect data in both mediums. VoiceEx was created to support a self-explanations intervention for computer science students; however, given its features and the advantages of being able to collect spoken responses, it can be used in a variety of environments. Future refinement of this tool includes artificial intelligence features to better guide students' submissions.
{"title":"VoiceEx: Voice Submission System for Interventions in Education","authors":"Angela Zavaleta Bernuy, Naaz Sibia, Pan Chen, Chloe Huang, Andrew Petersen, J. J. Williams, Michael Liut","doi":"10.1145/3587103.3595284","DOIUrl":"https://doi.org/10.1145/3587103.3595284","url":null,"abstract":"Generating self-explanations has been identified as a successful strategy in helping learners engage with course content and organize what they learn in a structured format. While typing an explanation may allow more structure and formality, explaining by voice can be more natural and help free cognitive resources to focus on learning goals and understanding concepts. As we investigated the effects and students' perceptions of using voice or text to self-explain new course concepts, we failed to find a tool that would meet our needs. We present our work in designing and developing VoiceEx, a submission courseware that allows text and voice input to collect data in both mediums. VoiceEx was created to support a self-explanations intervention for computer science students; however, given its features and the advantages of being able to collect spoken responses, it can be used in a variety of environments. Future refinement of this tool includes artificial intelligence features to better guide students' submissions.","PeriodicalId":366365,"journal":{"name":"Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116208821","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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