Real-Time Learning Analytics Dashboard for Students in Online Classes

Author(s):  
Takuro Owatari ◽  
Atsushi Shimada ◽  
Tsubasa Minematsu ◽  
Maiya Hori ◽  
Rin-ichiro Taniguchi
2018 ◽  
Vol 3 (1) ◽  
pp. 43
Author(s):  
Sinta Dewi Ratnawati

This English for Specific/Occupational Purpose (ESP/EOP) program was meant to answer the needs of the Indonesian migrant labourers to improve their English for future employment as tour guides. The objectives of this research were to identify the contents that should be in the materials, to investigate the students’ response about the later developed materials, and to study the lacks in the program. The material development process underwent the 7 stages of material development proposed by Nation and Macalister (2010), consisted of analysing the environment and the needs, following principles, setting goals and objectives, choosing contents and sequence, finding the format and presentation, monitoring and assessing, and evaluating the course. However, since it is online learning, the stages had to be combined with the stages specifically for online materials proposed by Hartoyo (2012). Thus, the content and sequence choosing stage consisted of the selection of the types of program, materials, software and tasks. The materials consisted of 2 parts which were the tutorials and the lessons. Using the Task-Based Language Teaching approach (Nunan, 2004), the materials were developed and implemented combined with real time online classes. The students’ responses after the implementation were generally positive, although some improvements were still needed.   Keywords: English for specific purpose (ESP), English for occupational purpose (EOP), material development, online learning, English for tour guides, Task-Based Language Teaching (TBLT)


2021 ◽  
Vol 15 (5) ◽  
pp. 113-128
Author(s):  
Yun-Bin Lee

The purpose of this study is to construct and propose real-time online college writing teaching methods to promote interaction between class members (instructor-learner, learner-learner). Through surveys and interviews with learners who hadn’t experienced real-time, online college writing education, we confirmed that the main perceptions and demands of learners for real-time online classes were as follows: First, the learners’ reluctance to show oneself in such a class and the demand for interaction with minimal online exposure. Second, the burden of writing in an isolated environment and the demand for detailed assistance of instructor’s in the writing process. Third, the reluctance to show the learner’s written text and the demand for receiving sufficient feedback anonymously. Therefore, this study proposed the following three teaching methods: First, a method to ensure learner anonymity to allow learners to participate in classes using a “sub-character” rather than their real names. Second, to conduct a short [lecture-practice-feedback] method, instead of a one-time [lecture-practice] method, was implemented several times in one class. Thirdly, to simultaneously share the learners' practice results through chat windows and to provide multiple types of feedback. This study confirmed that the proposed methods promote interaction between members in an online writing education environment and generate positive teaching and learning effects by reviewing specific class application cases and the learners' responses to these classes.


2020 ◽  
Vol 13 (4) ◽  
pp. 790-803
Author(s):  
Kai Liu ◽  
Sivanagaraja Tatinati ◽  
Andy W. H. Khong

2020 ◽  
Vol 37 (5) ◽  
pp. 267-277
Author(s):  
Maarten de Laat ◽  
Srecko Joksimovic ◽  
Dirk Ifenthaler

PurposeTo help workers make the right decision, over the years, technological solutions and workplace learning analytics systems have been designed to aid this process (Ruiz-Calleja et al., 2019). Recent developments in artificial intelligence (AI) have the potential to further revolutionise the integration of human and artificial learning and will impact human and machine collaboration during team work (Seeber et al., 2020).Design/methodology/approachComplex problem-solving has been identified as one of the key skills for the future workforce (Hager and Beckett, 2019). Problems faced by today's workforce emerge in situ and everyday workplace learning is seen as an effective way to develop the skills and experience workers need to embrace these problems (Campbell, 2005; Jonassen et al., 2006).FindingsIn this commentary the authors argue that the increased digitization of work and social interaction, combined with recent research on workplace learning analytics and AI opens up the possibility for designing automated real-time feedback systems capable of just-in-time, just-in-place support during complex problem-solving at work. As such, these systems can support augmented learning and professional development in situ.Originality/valueThe commentary reflects on the benefits of automated real-time feedback systems and argues for the need of shared research agenda to cohere research in the direction of AI-enabled workplace analytics and real-time feedback to support learning and development in the workplace.


Author(s):  
Gregor Kennedy ◽  
Ioanna Ioannou ◽  
Yun Zhou ◽  
James Bailey ◽  
Stephen O'Leary

<p>The analysis and use of data generated by students’ interactions with learning systems or programs – learning analytics – has recently gained widespread attention in the educational technology community. Part of the reason for this interest is based on the potential of learning analytic techniques such as data mining to find hidden patterns in students’ online interactions that can be meaningfully interpreted and then fed back to students in a way that supports their learning. In this paper we present an investigation of how the digital data records of students’ interactions within an immersive 3D environment can be mined, modeled and analysed, to provide real-time formative feedback to students as they complete simulated surgical tasks. The issues that emerged in this investigation as well as areas for further research and development are discussed.</p>


2019 ◽  
Vol 6 (2) ◽  
Author(s):  
Kenneth Holstein ◽  
Bruce M. McLaren ◽  
Vincent Aleven

Involving stakeholders throughout the creation of new educational technologies can help ensure their usefulness and usability in real-world contexts. However, given the complexity of learning analytics (LA) systems, it can be challenging to meaningfully involve non-technical stakeholders throughout their design and development. This article reports on the iterative co-design, development, and classroom evaluation of Konscia, a wearable, real-time awareness tool for teachers working in AI-enhanced K-12 classrooms. In the process, we argue that the co-design of LA systems requires new kinds of prototyping methods. We introduce one of our own prototyping methods, REs, to address unique challenges of co-prototyping LA tools. This work presents the first end-to-end demonstration of how non-technical stakeholders can participate throughout the whole design process for a complex LA system—from early generative phases to the selection and tuning of analytics to evaluation in real-world contexts. We conclude by providing methodological recommendations for future LA co-design efforts.


2018 ◽  
Vol 15 (4) ◽  
pp. 314-331 ◽  
Author(s):  
Atsushi Shimada ◽  
Shin’ichi Konomi ◽  
Hiroaki Ogata

Purpose The purpose of this study is to propose a real-time lecture supporting system. The target of this study is on-site classrooms where teachers give lectures and a lot of students listen to teachers’ explanations, conduct exercises, etc. Design/methodology/approach The proposed system uses an e-learning system and an e-book system to collect teaching and learning activities from a teacher and students in real time. The collected data are immediately analyzed to provide feedback to the teacher just before the lecture starts and during the lecture. For example, the teacher can check which pages were well previewed and which pages were not previewed by students using the preview achievement graph. During the lecture, real-time analytics graphs are shown on the teacher’s PC. The teacher can easily grasp students’ status and whether or not students are following the teacher’s explanation. Findings Through the case study, the authors first confirmed the effectiveness of each tool developed in this study. Then, the authors conducted a large-scale experiment using a real-time analytics graph and investigated whether the proposed system could improve the teaching and learning in on-site classrooms. The results indicated that teachers could adjust the speed of their lecture based on the real-time feedback system, which also resulted in encouraging students to put bookmarks and highlights on keywords and sentences. Originality/value Real-time learning analytics enables teachers and students to enhance their teaching and learning during lectures. Teachers should start considering this new strategy to improve their lectures immediately.


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