Learning: Research and Practice最新文献

{"title":"A case study of designing technology-enhanced learning in an elementary school in Singapore","authors":"L. Tay, Mohamed Melwani, Jemuel Liangyu Ong, Ken Renjie Ng","doi":"10.1080/23735082.2017.1350737","DOIUrl":"https://doi.org/10.1080/23735082.2017.1350737","url":null,"abstract":"ABSTRACT This case study presents how teachers from an elementary school in Singapore design learning for their students, leveraging on the use of information and communications technology (ICT). The school in this case study is one of the eight future schools in Singapore under the FutureSchools@Singapore programme. The school provides one-to-one computing learning devices and wireless Internet access for its students. Teachers from the school, teaching various grade levels and subject matters, were interviewed on how they use current and prevalent online technologies to enhance and transform teaching practices. In-depth discussion interviews with the teachers about their pedagogical practices were analysed according to the six learning experiences – acquisition, inquiry, practice, production, discussion and collaboration. Structural elements surrounding this case study (e.g. conditions surrounding the school) were also taken into consideration. The rich description and in-depth interviews with the teachers can also provide models for other teachers to emulate and reflect upon. This case study highlights the following: pedagogical differences and similarities in different subject areas, that students’ learning experience depends on how lessons are being designed, structural elements that affect ICT use and integration, and the need for students to learn to use before they can use ICT to learn.","PeriodicalId":52244,"journal":{"name":"Learning: Research and Practice","volume":"20 1","pages":"113 - 98"},"PeriodicalIF":0.0,"publicationDate":"2017-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80315583","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}

{"title":"Kids in the capitol: improving civic literacy through experiential learning","authors":"D. Fudge, S. Skipworth","doi":"10.1080/23735082.2017.1349169","DOIUrl":"https://doi.org/10.1080/23735082.2017.1349169","url":null,"abstract":"ABSTRACT The contemporary education system aides in the development of students’ cognitive learning skills to better prepare them for the future; however, education can also prepare students to be more engaged citizens in a democratic society. Civic literacy is a valuable skill for students to learn as it provides a foundation for a better understanding of the complexities of government and the political world. Experiential learning through educational field trips has been proven to stimulate an increased awareness of particular concepts and ideas. In this brief commentary, we demonstrate that civic literacy can be promoted in the minds of young students by exposing them first-hand to the political process. Furthermore, the current understanding of civic literacy is lacking and requires innovative methods to better facilitate learning outcomes that will not only benefit learning outcomes but future civic engagement.","PeriodicalId":52244,"journal":{"name":"Learning: Research and Practice","volume":"33 1","pages":"163 - 167"},"PeriodicalIF":0.0,"publicationDate":"2017-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78357386","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}

{"title":"Social influences on student perceptions of failure in learning design processes: instructional implications","authors":"M. Tan, S. Lee, Zhi Ying Ng","doi":"10.1080/23735082.2017.1351577","DOIUrl":"https://doi.org/10.1080/23735082.2017.1351577","url":null,"abstract":"ABSTRACT While the Silicon Valley aphorism would encourage all involved in design to ‘fail early so that one can succeed earlier’, such a concept may be hard to translate to classroom instructional strategies, especially due to the negative connotations of failure in school settings. Failures in design serve a somewhat distinct purpose from failures in schooling; however, for learners, this distinction is hard to distinguish, and the subjective experiencing of these forms can be highly similar. In this paper, we discuss the role of failure in learning, especially in the design process. We examine the ethnographic case study of a grade nine class involved in a design instruction course, and find that while students were aware of the positive attributes of failure, they had difficulty embracing failure as a classroom activity, and take risks to accomplish projects. We trace these perceptions to the social messaging around failure that these students experience, and discuss some implications these findings may have for failure, risk aversion, and ultimately, schools as sites for educating innovativeness in societies.","PeriodicalId":52244,"journal":{"name":"Learning: Research and Practice","volume":"27 1","pages":"130 - 147"},"PeriodicalIF":0.0,"publicationDate":"2017-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81466807","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}

{"title":"Deepening and transferring twenty-first century learning through a lower secondary Integrated Science module","authors":"Fong Kwan Thang, J. Koh","doi":"10.1080/23735082.2017.1335426","DOIUrl":"https://doi.org/10.1080/23735082.2017.1335426","url":null,"abstract":"ABSTRACT A secondary school in Singapore incorporated twenty-first century learning into their science curriculum through an inquiry-based Integrated Science module. This study examines Secondary 2 students’ perceptions of twenty-first century learning through this module. Through pre- and post-study surveys of 227 students and focus group interviews with nine students, it was found that the Integrated Science module deepened students’ confidence with self-directed learning and authentic problem-solving whereas students’ confidence with critical thinking positively predicted students’ end-of-year results. Through this module, students acquired skills related to time management, information analysis, the use of information communications technologies and presentation that they transferred to the learning of their other academic subjects. The implications for designing twenty-first century learning experiences in schools are discussed.","PeriodicalId":52244,"journal":{"name":"Learning: Research and Practice","volume":"100 1","pages":"148 - 162"},"PeriodicalIF":0.0,"publicationDate":"2017-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78094900","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}

{"title":"Expediting the cycle of data to intervention","authors":"C. Rosé","doi":"10.1080/23735082.2017.1286140","DOIUrl":"https://doi.org/10.1080/23735082.2017.1286140","url":null,"abstract":"An important research problem in learning analytics is to expedite the cycle of data leading to the analysis of student needs and the improvement of student support. Current work in Learning Analytics and Educational Data Mining provides many examples where machine learning applied to learning relevant data produces models that can teach us about learning processes as well as trigger just-in-time interventions. Though the technology is still young, the time is ripe to look to the future where such learned models will enable personalised experiences to learners at a grand scale. In our own research, we have focused on learning through discussion (Howley & Rosé, in press). In this space, the subfield of Discourse Analytics (Buckingham-Shum, 2013; Buckingham-Shum, De Laat, De Liddo, Ferguson, & Whitelock, 2014; Rosé, in press) provides examples where models with high utility can be learned even over messy, relatively unstructured discourse data. The substantive problems that must be overcome to build effective, interpretable, and actionable models over Discourse data are the continuing focus of work in the area of Discourse Analytics. Beyond this, however, is the more focused, but nevertheless necessary issue of creating a data infrastructure and pipeline specifically targeting this rich but challenging data (Jo, Tomar, Ferschke, Rosé, & Gaesevic, 2016). The foundation of computational analytic work is representation of data. Much of our published work in analytics of collaboration in discussion has been focused on either chat data (Howley, Mayfield, & Rosé, 2013) or transcribed face-to-face discussion (Ai, Sionti, Wang, & Rosé, 2010; Clarke et al., 2013). These can both be represented in a simple, uniform, flat sequence of text segments, each contributed by one speaker. However, when expanding to learning in Massive Open Online Courses (MOOCs) or learning in other online contexts such as opensource communities, the form that the discussions may take becomes more diverse as they are embedded in a variety of platforms. They may even occur simultaneously through multiple separate streams. To that end we offer a publically available data infrastructure we call DiscourseDB, which enables translation of data from multiple streams into a common, integrated representation. The interface level representation is translated down into Discourses, with embedded Discourse Parts consisting of Contributions, which may be related to one another through Relations, and which are associated with content that can be associated with Annotations. This common representation enables combining data across communication streams and applying common modelling technologies. As a concrete example, consider connectivist Massive Open Online Courses (cMOOCs) that include environments like the competency-based learning platform ProSolo, featured in a recent edX MOOC called Data, Analytics, and Learning (DALMOOC) (Rosé et al., 2015). In these environments data is rich and heterogeneo","PeriodicalId":52244,"journal":{"name":"Learning: Research and Practice","volume":"30 1","pages":"59 - 62"},"PeriodicalIF":0.0,"publicationDate":"2017-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87725774","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}

{"title":"Understanding idea flow: applying learning analytics in discourse","authors":"A. Lee, S. Tan","doi":"10.1080/23735082.2017.1283437","DOIUrl":"https://doi.org/10.1080/23735082.2017.1283437","url":null,"abstract":"ABSTRACT The assessment and understanding of students’ ideas in discourse have often been a difficult problem for teachers to tackle. Recent innovations and technologies such as text mining can provide a partial solution by generating an estimated count of important keywords which are representative of ideas within discourse. However, investigating idea development and flow within discourse is a much more challenging task, and requires elaborate processing and analysis. In this study, a method for analysing idea flow was proposed and tested: (1) text mining and network analysis are employed to identify and validate ideas from textual discourse; (2) identified ideas are grouped together and mapped to relevant learning objectives; (3) groups of ideas are then aggregated using a binning method and scored; (4) a flow diagram is generated using the aggregated scores to visualise idea flow within discourse. By understanding how ideas flow within discourse, discussed key ideas can be monitored and any lapses in student understanding can be identified so that teachers will have information to provide timely interventions to support and scaffold learning.","PeriodicalId":52244,"journal":{"name":"Learning: Research and Practice","volume":"41 1","pages":"12 - 29"},"PeriodicalIF":0.0,"publicationDate":"2017-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76052320","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}

{"title":"Situating learning analytics pedagogically: towards an ecological lens","authors":"J. Tan, Elizabeth Koh","doi":"10.1080/23735082.2017.1305661","DOIUrl":"https://doi.org/10.1080/23735082.2017.1305661","url":null,"abstract":"Learning Analytics (LA) is both a growing trend and an increasingly prominent feature of contemporary twenty-first century teaching and learning that has captured the attention and imaginations of ...","PeriodicalId":52244,"journal":{"name":"Learning: Research and Practice","volume":"11 1","pages":"1 - 11"},"PeriodicalIF":0.0,"publicationDate":"2017-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89008642","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}

{"title":"Measuring teacher sense making strategies of learning analytics: a case study","authors":"Anouschka van Leeuwen, M. van Wermeskerken, G. Erkens, N. Rummel","doi":"10.1080/23735082.2017.1284252","DOIUrl":"https://doi.org/10.1080/23735082.2017.1284252","url":null,"abstract":"ABSTRACT Teacher orchestration of the classroom is a demanding task because of the multitude of activities and the rapid pace at which these activities occur. Teachers must constantly be aware of the activities students engage in and the progress students are making, in order to be able to make informed decisions. Recent years have seen the development of learning analytics (LA) to support teachers, in the form of interfaces that capture and visualise data about learner activities. LA are hypothesised to deliver actionable knowledge, because the provided information would enable teachers to immediately translate the information into concrete intervention of some kind. This paper provides a short discussion of the hypothesised affordances of LA for supporting teachers, and subsequently, a case study is presented in which a teacher’s sense making strategies of LA were investigated within a digital environment, which enabled the teacher to monitor and regulate the activities of five collaborating groups of students. Besides automatically logged teacher behaviour, eye tracking was used to examine eye movements, and cued retrospective reporting was used to evaluate the choices and decisions made by the teacher. The case study is used to discuss directions for future research concerning learning analytics to support teachers.","PeriodicalId":52244,"journal":{"name":"Learning: Research and Practice","volume":"110 1","pages":"42 - 58"},"PeriodicalIF":0.0,"publicationDate":"2017-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87583703","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}

{"title":"Piecing the learning analytics puzzle: a consolidated model of a field of research and practice","authors":"D. Gašević, Vitomir Kovanovíc, Srécko Joksimovíc","doi":"10.1080/23735082.2017.1286142","DOIUrl":"https://doi.org/10.1080/23735082.2017.1286142","url":null,"abstract":"ABSTRACT The field of learning analytics was founded with the goal to harness vast amounts of data about learning collected by the extensive use of technology. After the early formation, the field has now entered the next phase of maturation with a growing community who has an evident impact on research, practice, policy, and decision-making. Although learning analytics is a bricolage field borrowing from many related other disciplines, there is still no systematised model that shows how these different disciplines are pieced together. Existing models and frameworks of learning analytics are valuable in identifying elements and processes of learning analytics, but they insufficiently elaborate on the links with foundational disciplines. With this in mind, this paper proposes a consolidated model of the field of research and practice that is composed of three mutually connected dimensions – theory, design, and data science. The paper defines why and how each of the three dimensions along with their mutual relations is critical for research and practice of learning analytics. Finally, the paper stresses the importance of multi-perspective approaches to learning analytics based on its three core dimensions for a healthy development of the field and a sustainable impact on research and practice.","PeriodicalId":52244,"journal":{"name":"Learning: Research and Practice","volume":"9 1","pages":"63 - 78"},"PeriodicalIF":0.0,"publicationDate":"2017-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78919693","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}

{"title":"Learning is the key twenty-first century skill","authors":"D. Kuhn","doi":"10.1080/23735082.2016.1205207","DOIUrl":"https://doi.org/10.1080/23735082.2016.1205207","url":null,"abstract":"ABSTRACT Why are some people more effective learners than others? Despite the centrality of learning to life success, solid, comprehensive answers to this question do not yet exist. Global ability constructs do not provide adequate answers, and the case is made here for the need to go beyond them to closely examine the learning process itself and the multiple skills and dispositions that contribute to it. Only equipped with such knowledge can we understand individual differences in learning and be able to use this understanding to help all students become better learners.","PeriodicalId":52244,"journal":{"name":"Learning: Research and Practice","volume":"95 1","pages":"88 - 99"},"PeriodicalIF":0.0,"publicationDate":"2016-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82077602","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}