Books and editorial works
Gašević, D., Tsai, Y. S., and Drachsler, H. (Ed.) (2021). Learning Analytics in Higher Education –Stakeholders, Strategies, and Scale (Special Issue). The Internet and Higher Education.
Tsai, Y. S. (2016).《ti VUVU katua Vatu katua ngiaw 公公、狗和貓–懷約翰傳記》(Translation: Grandpa, Dog and Cat–the Biography of John Whitehorn). Taiwan Church Press. 296 pages.
Reverend John Whitehorn came to Taiwan in 1951 to assist the work of bible translation in a tribal language, Paiwanese. He dedicated more than 20 years to this work, and published two Paiwanese bibles in 1973 and 1993 respectively, in addition to a linguistic book in 2013 – “One Hundred Paiwan Texts”. This biography records his life stories based on his personal memoirs and a number of interviews with him and his family.
Journal articles
Hassan Khosravi, Simon Buckingham Shum, Guanliang Chen, Cristina Conati, Yi-Shan Tsai, Judy Kay, Simon Knight, Roberto Martinez-Maldonado, Shazia Sadiq, Dragan Gašević (2022). Explainable Artificial Intelligence in education. Computers and Education: Artificial Intelligence, 3. (Author version)
There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of educational interventions supported by the use of Artificial Intelligence (AI) algorithms. One of the emerging methods for increasing trust in AI systems is to use eXplainable AI (XAI), which promotes the use of methods that produce transparent explanations and reasons for decisions AI systems make. Considering the existing literature on XAI, this paper argues that XAI in education has commonalities with the broader use of AI but also has distinctive needs. Accordingly, we first present a framework, referred to as XAI-ED, that considers six key aspects in relation to explainability for studying, designing and developing educational AI tools. These key aspects focus on the stakeholders, benefits, approaches for presenting explanations, widely used classes of AI models, human-centred designs of the AI interfaces and potential pitfalls of providing explanations within education. We then present four comprehensive case studies that illustrate the application of XAI-ED in four different educational AI tools. The paper concludes by discussing opportunities, challenges and future research needs for the effective incorporation of XAI in education.
Gašević, D., Tsai, Y. S., & Drachsler, H. (2022). Learning analytics in higher education–Stakeholders, strategy and scale. The Internet and Higher Education, 52 (Editorial). (Author version)
In response to several open challenges in learning analytics, this special issue aims to address stakeholder perspectives and involvement, strategy development and enactment, and scalable implementations.
Carvalho, L., Martinez-Maldonado, R., Tsai, Y. S., Markauskaite, L., & De Laat, M. (2022). How can we design for learning in an AI world?. Computers and Education: Artificial Intelligence, 3, 100053. (Author version)
Fast improvements in computing power and Artificial Intelligence (AI) algorithms enable us to automate important decisions that shape our everyday lives, and drive workplace transformations. It is predicted that many people will find themselves unprepared to deal with high degrees of change and uncertainty, increasingly posed by AI in some sectors. A critical educational challenge involves figuring out how to support young generations to develop the capabilities that they will need to adapt to, and innovate in, a world with AI. This article argues that both educators and learners should be involved not only in learning but also in co-designing for learning in an AI world. Further, they together should explore the knowledge, goals and actions that could help people shape future AI scenarios, and learn to deal with high degrees of uncertainty. A key contribution of the paper is a re-conceptualization of design for learning in an AI world, which explores a problem space of educational design, and illustrates how educators and learners can work together to re-imagine education futures in an AI world. As part of this problem space, the paper discusses underpinning philosophies (the capability approach and value creation), a high-level pedagogy (with an emphasis on co-creation), pedagogical strategies (speculative pedagogies), and pedagogical tactics (AI scenarios). It then proposes a design framework (ACAD) to support educators and learners’ discussions about design for learning in an AI world. This participatory design approach aims to sensitize people for what education may mean, for whom, and how learning with AI may look like, and it highlights the active engagement of educators and learners in co-designing a future they desire, to help shape learning and living in an AI world.
Muñoz-Merino, P. J., Moreno-Marcos, P. M., Rubio-Fernández, A., Tsai, Y. S., Gašević, D., & Delgado Kloos, C. (2022). A systematic analysis of learning analytics using multi-source data in the context of Spain. Behaviour & Information Technology, 1-15. (Author version)
Learning analytics (LA) employs educational data to improve the timeliness of support for learners. Apart from technical aspects, there is a need to understand social complexities brought about by different stakeholders, so as to systematise the adoption of LA in Higher Education (HE). We present an analysis of the situation, needs and challenges of LA in the context of Spanish HE, considering managers’, teachers’ and students’ perspectives. Qualitative research is employed using recursive abstraction. Results reveal that the level of institutional adoption is low and none of the analysed institutions had an LA policy. Furthermore, only two of these institutions had an initial LA strategy. While the institutions shared some commonalities in their objectives for LA, chosen tools and adoption challenges, the distinct differences in the political contexts and institutional practices among the institutions reaffirmed that LA solutions and services cannot be implemented in the same manner. Moreover, different needs for LA and concerns are identified about its adoption among managers, students and teachers. These observations lead to our conclusion that the main challenges to implement LA in Spain are not related to technological issues but to the social and cultural issues rooted in institutions and those associated with different stakeholders.
Tsai, Y. S., Whitelock-Wainwright, A., & Gašević, D. (2021). More Than Figures on Your Laptop: (Dis)trustful Implementation of Learning Analytics. Journal of Learning Analytics, 8(3), 81-100 . (Author version)
The adoption of learning analytics (LA) in complex educational systems is woven into sociocultural and technical challenges that have induced distrust in data and difficulties in scaling LA. This paper presents a study that investigated areas of distrust and threats to trustworthy LA through a series of consultations with teaching staff and students at a large UK university. Surveys and focus groups were conducted to explore participant expectations of LA. The observed distrust is broadly attributed to three areas: the subjective nature of numbers, the fear of power diminution, and approaches to design and implementation of LA. The paper highlights areas to maintain existing trust with policy procedures and areas to cultivate trust by engaging with tensions arising from the social process of LA.
Cavalcanti, A. P., Barbosa, A., Carvalho, R., Freitas, F., Tsai, Y. S., Gašević, D., & Mello, R. F. (2021). Automatic feedback in online learning environments: A systematic literature review. Computers and Education: Artificial Intelligence. (Author version)
Feedback is an essential component of scaffolding for learning. Feedback provides insights into the assistance of learners in terms of achieving learning goals and improving self-regulated skills. In online courses, feedback becomes even more critical since instructors and students are separated geographically and physically. In this context, feedback allows the instructor to customize learning content according to the students’ needs. However, giving feedback is a challenging task for instructors, especially in contexts of large cohorts. As a result, several automatic feedback systems have been proposed to reduce the workload on the part of the instructor. Although these systems have started gaining research attention, there have been limited studies that systematically analyze the progress achieved so far as reported in the literature. Thus, this article presents a systematic literature review on automatic feedback generation in learning management systems. The main findings of this review are: (1) 65.07% of the studies demonstrate that automatic feedback increases student performance in activities; (2) 46.03% of the studies demonstrated that there is no evidence that automatic feedback eases instructors’ workload; (3) 82.53% of the studies showed that there is no evidence that manual feedback is more efficient than automatic feedback; and (4) the main method used for automatic feedback provision is the comparison with a desired answer in some subject (such as logic circuits or programming).
Tsai, Y. S., Kovanović, V., & Gašević, D. (2021). Connecting the dots: An exploratory study on learning analytics adoption factors, experience, and priorities. The Internet and Higher Education. (Author version)
Existing studies have shed light on policies and strategies for
learning analytics (LA) adoption, yet there is limited understanding of associations among factors that influence adoption processes or the change in priorities when institutional experience with LA increases. This paper addresses this gap by presenting a study based on interviews with institutional leaders from 27 European higher education institutions. Results showed that experienced institutions demonstrated more interest in exploring learning behaviour and pedagogical reformation than simply measuring a phenomenon. Experienced institutions also paid more attention to methodological approaches to LA than data constraints, and demonstrated a broader involvement of teachers and students. This paper also identifies inter-related connections between prevailing challenges that impede the scaling of LA. Based on the results, we suggest regular evaluations of LA adoption to ensure the alignment of strategy and desired changes. We also identify three areas that require particular attention when forming short-term goals for LA at different phases of adoption
Kollom, K., Tammets, K., Scheffel, M., Tsai, Y. S., Jivet, I., Muñoz-Merino, P. J., … & Ley, T. (2021). A four-country cross-case analysis of academic staff expectations about learning analytics in higher education. The Internet and Higher Education. (Author version)
The purpose of this paper is to explore the expectations of academic staff to learning analytics services from an ideal as well as a realistic perspective. This mixed-method study focused on a cross-case analysis of staff from Higher Education Institutions from four European universities (Spain, Estonia, Netherlands, UK). While there are some differences between the countries as well as between ideal and predicted expectations, the overarching results indicate that academic staff sees learning analytics as a tool to understand the learning activities and possibility to provide feedback for the students and adapt the curriculum to meet learners’ needs. However, one of the findings from the study across cases is the generally consistently low expectation and desire for academic staff to be obligated to act based on data that shows students being at risk of failing or under-performing.
Whitelock-Wainwright, A., Tsai, Y. S., Drachsler, H., Scheffel, M., & Gašević, D. (2021). An exploratory latent class analysis of student expectations towards learning analytics services. The Internet and Higher Education. (Author version)
The purpose of this paper is to explore the expectations of academic staff to learning analytics services from an ideal as well as a realistic perspective. This mixed-method study focused on a cross-case analysis of staff from Higher Education Institutions from four European universities (Spain, Estonia, Netherlands, UK). While there are some differences between the countries as well as between ideal and predicted expectations, the overarching results indicate that academic staff sees learning analytics as a tool to understand the learning activities and possibility to provide feedback for the students and adapt the curriculum to meet learners’ needs. However, one of the findings from the study across cases is the generally consistently low expectation and desire for academic staff to be obligated to act based on data that shows students being at risk of failing or under-performing.
Tsai, Y. S., Rates, D., Moreno-Marcos, P. M., Muñoz-Merino, P. J., Jivet, I., Scheffel, M., … & Gašević, D. (2020). Learning analytics in European higher education–trends and barriers. Computers & Education. (Author version)
Learning analytics (LA) as a research field has grown rapidly over the last decade. However, adoption of LA is mostly found to be small in scale and isolated at the instructor level. This paper presents an exploratory study on institutional approaches to LA in European higher education and discusses prominent challenges that impede LA from reaching its potential. Based on a series of consultations with senior managers from 83 different higher education institutions in 24 European countries, we observe that LA is primarily perceived as a tool to enhance teaching and institutional management. As a result, teaching and support staff are found to be the main users of LA and the target audience of training support. In contrast, there is little evidence of active engagement with students or using LA to develop self-regulated learning skills. We highlight the importance of grounding LA in learning sciences and including students as a key stakeholder in the design and implementation of LA. This paper contributes to our understanding of the development of LA in European higher education and highlights areas to address in both practice and research.
Matcha, W., Gasevic, D., Uzir, N. A. A., Jovanovic, J., Pardo, A., Lim, L., … & Tsai, Y. S. (2020). Analytics of Learning Strategies: Role of Course Design and Delivery Modality. Journal of Learning Analytics, 7(2), 45-71.
Generalizability of the value of methods based on learning analytics remains one of the big challenges in the field of learning analytics. One approach to testing generalizability of a method is to apply it consistently in different learning contexts. This study extends a previously published work by examining the generalizability of a learning analytics method proposed for detecting learning tactics and strategies from trace data. The method was applied to the datasets collected in three different course designs and delivery modalities, including flipped classroom, blended learning, and massive open online course. The proposed method combines process mining and sequence analysis. The detected learning strategies are explored in terms of their association with academic performance. The results indicate the applicability of the proposed method across different learning contexts. Moreover, the findings contribute to the understanding of the learning tactics and strategies identified in the trace data: learning tactics proved to be responsive to the course design, whereas learning strategies were found to be more sensitive to the delivery modalities than to the course design. These findings, well aligned with self-regulated learning theory, highlight the association of learning contexts with the choice of learning tactics and strategies.
Hilliger, I., Ortiz‐Rojas, M., Pesántez‐Cabrera, P., Scheihing, E., Tsai, Y. S., Muñoz‐Merino, P. J., … & Pérez‐Sanagustín, M. (2020). Towards learning analytics adoption: A mixed methods study of data-related practices and policies in Latin American universities. British Journal of Educational Technology, 51(4):915–937, 2020. (Author version)
In Latin American universities, Learning Analytics (LA) has been perceived as a promising opportunity to leverage data to meet the needs of a diverse student cohort. Although universities have been collecting educational data for years, the adoption of LA in this region is still limited due to the lack of expertise and policies for processing and using educational data. In order to get a better picture of how existing data-related practices and policies might affect the incorporation of LA in Latin American institutions, we conducted a mixed-methods study in four Latin American universities (two Chilean and two Ecuadorian). In this paper, the qualitative data is based on 37 interviews with managers and 16 focus groups with 51 teaching staff and 45 students; the quantitative data was collected through two surveys answered by 1,884 students and 368 teachers respectively. The findings reveal opportunities to incorporate LA services into existing data practices in the four case studies. However, the lack of reliable information systems and policies to regulate the use of data imposes challenges that need to be overcome for future LA adoption.
Isabel Hilliger, Margarita Ortiz-Rojas, Paola Pesántez-Cabrera, Eliana Scheihing, Yi-Shan Tsai, Pedro J. Mu ̃noz-Merino, Tom BHilliger, I., Ortiz-Rojas, M., Pesántez-Cabrera, P., Scheihing, E., Tsai, Y. S., Muñoz-Merino, P. J., … & Pérez-Sanagustín, M. (2020). Identifying needs for learning analytics adoption in Latin American universities: A mixed-methods approach. The Internet and Higher Education. (Author version)
Learning Analytics (LA) is perceived to be a promising strategy to tackle persisting educational challenges in Latin America, such as quality disparities and high dropout rates. However, Latin American universities have fallen behind in LA adoption compared to institutions in other regions. To understand stakeholders’ needs for LA services, this study used mixed methods to collect data in four Latin American Universities. Qualitative data was obtained from 37 interviews with managers and 16 focus groups with 51 teaching staff and 45 students, whereas quantitative data was obtained from surveys answered by 1884 students and 368 teaching staff. According to the triangulation of both types of evidence, we found that (1) students need quality feedback and timely support, (2) teaching staff need timely alerts and meaningful performance evaluations, and (3) managers need quality information to implement support interventions. Thus, LA offers an opportunity to integrate data-driven decision-making in existing tasks.
Tsai, Y. S., Perrotta, C., & Gašević, D. (2020). Empowering learners with personalised learning approaches? agency, equity and transparency in the context of learning analytics. Assessment and Evaluation in Higher Education, 45(4): 554-567. (Author version)
In this paper, we discuss the tensions between using learning analytics to increase student agency in making learning-related decisions while ‘datafying’ students in the process of collecting, analysing and interpreting data. This paper explores staff and student experience of agency, equity, and transparency in existing data practices and expectations towards learning analytics in a UK university. This paper argues that learner empowerment should not be automatically assumed to have taken place as part of the adoption of learning analytics. Instead, the interwoven power relationships in a complex educational system and the interactions between humans and machines need to be taken into consideration when presenting LA as an equitable process to enhance student agency and educational equity.
Whitelock‐Wainwright, A., Gašević, D., Tsai, Y. S., Drachsler, H., Scheffel, M., Muñoz‐Merino, P. J., … & Delgado Kloos, C. (2020). Assessing the validity of a learning analytics expectation instrument: A multinational study. Journal of Computer Assisted Learning, 36(2): 209-240. (Author version)
To assist Higher Education Institutions in meeting the challenge of limited student engagement in the implementation of Learning Analytics services, the Questionnaire for Student Expectations of Learning Analytics (QSELA) was developed. This instrument contains 12 items, which are explained by a purported two-factor structure of Ethical and Privacy Expectations and Service Expectations. As it stands, however, the QSELA has only been validated with students from UK University students, which is problematic on account of the interest in Learning Analytics extending beyond this context. Thus, the aim of the current work was to assess whether the translated QSELA can be validated in three contexts (an Estonian, a Spanish, and a Dutch University). The findings show that the model provided acceptable fits in both the Spanish and Dutch samples, but was not supported in the Estonian student sample. In addition, an assessment of local fit is undertaken for each sample, which provides important points that need to be considered in future work. Finally, a general comparison of expectations across contexts is undertaken, which are discussed in relation to the General Data Protection Regulation (GDPR, 2018).
Tsai, Y. S., Poquet, O., Gašević, D., Dawson, S., & Pardo, A. (2019). Complexity leadership in learning analytics: Drivers, challenges, and opportunities. British Journal of Educational Technology, 50(6): 2839–2854. (Author version)
This paper examines LA adoption processes among 21 UK higher education institutions using complexity leadership theory as a framework. The data was collected from 23 interviews with institutional leaders and subsequently analysed using a thematic coding scheme. The results showed a number of prominent challenges associated with LA deployment, which lie in the inherent tensions between innovation and operation. These challenges require a new form of leadership to create and nurture an adaptive space in which innovations are supported and ultimately transformed into the mainstream operation of an institution. This paper argues that a complexity leadership model enables higher education to shift towards more fluid and dynamic approaches for LA adoption, thus ensuring its scalability and sustainability.
Gasevic, D., Tsai, Y. S., Dawson, S., & Pardo, A. (2019). How do we start? Directions for learning analytics adoption in higher education. International Journal of Information and Learning Technology, 36(4): 342–353. (Author version)
This paper addresses a commonly posed question asked by educators, managers, administrators, and researchers seeking to implement learning analytics – how do we start institutional adoption of learning analytics? The paper first defines learning analytics and touches on lessons learned from some well- known case studies. The paper then reviews the current state of institutional adoption of learning analytics by examining evidence produced in several studies conducted worldwide. The paper next outlines an approach to learning analytics adoption that could aid system-wide institutional transformation. The approach also highlights critical challenges that require close attention in order for learning analytics to make a long-term impact on research and practice of learning and teaching.
Whitelock‐Wainwright, A., Gašević, D., Tejeiro, R., Tsai, Y. S., & Bennett, K. (2019). The student expectations of learning analytics questionnaire (SELAQ). Journal of Computer Assisted Learning, 35(5): 633–666. (Author version)
This paper presents a descriptive instrument to measure student expectations (ideal and predicted) of learning analytics services. The scales used in the instrument have been grounded in theoretical framework of expectations, with a specific focus on ideal (hopes) and predicted (realistic beliefs) expectations. The results of an exploratory factor analysis and the results from both an exploratory structural equation model and confirmatory factor analysis supported a two-factor structure best accounted for the data pertaining to ideal and predicted expectations. Factor one refers to Ethical and Privacy Expectations, whilst factor two covers Service Feature Expectations. In addition, both scales (ideal and predicted) were found to have good internal reliability. The 12-item Student Expectations of Learning Analytics Questionnaire (SELAQ) provides researchers and practitioners with a reliable and valid instrument to collect quantitative measures of students’ expectations of learning analytics services.
Tsai, Y. S., Moreno-Marcos, P. M., Jivet, I., Scheffel, M., Tammets, K., Kollom, K., & Gašević, D. (2018). The SHEILA framework: Informing institutional strategies and policy processes of learning analytics. Journal of Learning Analytics, 5(3): 5–20. (Author version)
This paper introduces a learning analytics policy and strategy framework developed by a cross-European research project team — SHEILA (Supporting Higher Education to Integrate Learning Analytics), based on interviews with 78 senior managers from 51 European higher education institutions across 16 countries. The framework was developed adapting the RAPID Outcome Mapping Approach (ROMA), which is designed to develop effective strategies and evidence-based policy in complex environments. This paper presents four case studies to illustrate the development process of the SHEILA framework and how it can be used iteratively to inform strategic planning and policy processes in real world environments, particularly for large-scale implementation in higher education contexts. To this end, the selected cases were analyzed at two stages, each a year apart, to investigate the progression of adoption approaches that were followed to solve existing challenges, and identify new challenges that could be addressed by following the SHEILA framework.
Tsai, Y. S. (2018). Close-ups: an emotive language in manga. Journal of Graphic Novels and Comics, 9(5): 473–489. (Author version)
Manga is typically recognised in the Western world by the distinct visual styles of its characters and the vast array of symbolic signs that indicate various emotions and physical reactions. However, research into the use of visual techniques in the development of emotional life in manga is far from sufficient. This paper aims to explore the adoption of the cinematic technique – close-ups in manga – as a narrative tool to communicate a character’s emotions and build tension between panels. It draws examples from two manga and conversations with 16 young British readers to examine the impact of close shots on reader engagement.
Tsai, Y. S. (2016). The characteristics of manga fan communities–preliminary observations of 16 teenage manga readers in the UK. Journal of Graphic Novels and Comics, 7(4): 417–430. (Author version)
This article presents the results of a research project that explored young British readers’ engagement with manga in literary, aesthetic, social and cultural dimensions. Sixteen school pupils from two secondary schools participated in a number of inter- views to provide feedback on selected manga and their own participation in manga fandom. The results show that four distinct features characterise this particular cultural group, including exclusivity, competitiveness, defensiveness and trans-culturalism. This article aims to discuss these features by exploring the political roots of popular culture, the constant negotiation of power both outwardly and inwardly in fandom, and the fan’s desire to engage with an exotic culture through the text. It is noteworthy that the declaration of one’s identity as a manga fan shows a deep level of passion with which fans demonstrate confidence in their expertise and a determination to defend a taste that is considered illegitimate and degraded by institutional authorities.
Peer-reviewed proceedings
Tsai, Y. S. (2022). Why Feedback Literacy Matters for Learning Analytics. In the 16th International Conference of the Learning Sciences (ICLS) (pp. 27-34). (Author version)(ISLS 2022 Annual Meeting Proceedings)(ICLS 2022 proceedings)(arXiv)
Learning analytics (LA) provides data-driven feedback that aims to improve learning and inform action. For learners, LA-based feedback may scaffold self-regulated learning skills, which are crucial to learning success. For teachers, LA-based feedback may help the evaluation of teaching effects and the need for interventions. However, the current development of LA has presented problems related to the cognitive, social-affective, and structural dimensions of feedback. In light of this, this position paper argues that attention needs to shift from the design of LA as a feedback product to one that facilitates a process in which both teachers and students play active roles in meaning-making. To this end, implications for feedback literacy in the context of LA are discussed.
Tsai, Y. S., Singh, S., Rakovic, M., Lim, L. A., Roychoudhury, A. & Gašević, D. (2022). Charting Design Needs and Strategic Approaches for Academic Analytics Systems through Co-Design In LAK22: 12h International Learning Analytics and Knowledge Conference (pp. 175-185). (Author version)
Academic analytics focuses on collecting, analysing and visualising educational data to generate institutional insights and improve decision-making for academic purposes. However, challenges that arise from navigating a complex organisational structure when introducing analytics systems have called for the need to engage key stakeholders widely to cultivate a shared vision and ensure that implemented systems create desired value. This paper presents a study that takes co-design steps to identify design needs and strategic approaches for the adoption of academic analytics, which serves the purpose of enhancing the measurement of educational quality utilising institutional data. Through semi-structured interviews with 54 educational stakeholders at a large research university, we identified particular interest in measuring student engagement and the performance of courses and programmes. Based on the observed perceptions and concerns regarding data use to measure or evaluate these areas, implications for adoption strategy of academic analytics, such as leadership involvement, communication, and training, are discussed.
Pozdniakov, S., Martinez-Maldonado, R., Tsai, Y. S., Cukurova, M., Bartindale, T., Chen, P., Marshall, H., Richardson, D. & Gašević, D. (2022). The Question-driven Dashboard: How Can We Design Analytics Interfaces Aligned to Teachers’ Inquiry? In LAK22: 12h International Learning Analytics and Knowledge Conference (pp. 175-185). (Author version)
One of the ultimate goals of several learning analytics (LA) initiatives is to close the loop and support students’ and teachers’ reflective practices. Although there has been a proliferation of end-user interfaces (often in the form of dashboards), various limitations have already been identified in the literature such as key stakeholders not being involved in their design, little or no account for sense-making needs, and unclear effects on teaching and learning. There has been a recent call for human-centred design practices to create LA interfaces in close collaboration with educational stakeholders to consider the learning design, and their authentic needs and pedagogical intentions. This paper addresses the call by proposing a question-driven LA design approach to ensure that end-user LA interfaces explicitly address teachers’ questions. We illustrate the approach in the context of synchronous online activities, orchestrated by pairs of teachers using audio-visual and text-based tools (namely Zoom and Google Docs). This study led to the design and deployment of an open-source monitoring tool to be used in real-time by teachers when students work collaboratively in breakout rooms, and across learning spaces.
Alzahrani, A., Tsai, Y. S., Kovanović, V., Moreno-Marcos, P. M., Jivet, I., Aljohani, N., & Gašević, D. (2021, November). Success-Enablers of Learning Analytics Adoption in Higher Education: A Quantitative Ethnographic Study. In International Conference on Quantitative Ethnography (pp. 395-409). Springer, Cham. (Author version)
This paper focuses on the area of success-enablers in learning analytics (LA) adoption from the perspective of senior managers in higher education institutions (HEIs). A significant body of academic literature exists about challenges in LA. However, to date, the success-enablers from the perspectives of institutional senior managers have received limited attention. This research aims to address this gap reporting on the findings of a study that conducted a series of semi-structure interviews with senior managers at 44 European HEIs. A detailed thematic analysis was conducted on the interviews to tease out the main success-enablers. Then, connections of different success-enablers were analyzed using epistemic network analysis (ENA). The analysis showed that the success-enablers in HEIs that had fully adopted LA depended on the involvement of high-level stakeholders, setting an embedded strategy, getting a technology support from the external partnership, or having a strategic analytical culture. The HEIs that were preparing or only partly adopted LA depended on success-enablers such as having a developing analytical culture or a delegation of expertise in LA-related activity. The findings of this study can help HEIs create strategies that can support successful adoption of LA.
Tsai, Y. S., Mello, R. F., Jovanović, J., & Gašević, D. (2021, April). Student appreciation of data-driven feedback: A pilot study on OnTask. In LAK21: 11th International Learning Analytics and Knowledge Conference (pp. 511-517). (Author version)
Feedback plays a crucial role in student learning. Learning analytics (LA) has demonstrated potential in addressing prominent challenges with feedback practice, such as enabling timely feedback based on insights obtained from large data sets. However, there is insufficient research looking into relations between student expectations of feedback and their experience with LA-based feedback. This paper presents a pilot study that examined students’ experience of LA-based feedback, offered with the OnTask system, taking into consideration the factors of students’self-efficacy and self-regulation skills. Two surveys were carried out at a Brazilian university, and the results highlighted important implications for LA-based feedback practice, including leveraging the ‘partnership’ between the human teacher and the computer, and developing feedback literacy among learners.
Vemuri, P, Poelmans, S, van Rompaey, V, Tsai, YS, Brown, M & Gasevic, D 2021, Sustainable blended teaching practices: Lessons learned from instructor perspectives. In 18th International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2021. IADIS Press, pp. 345-349.
The higher education (HE) sector has undergone drastic changes due to the preventive measures needed to cope with the Covid-19 pandemic since March 2020. As a result, most traditional classroom teaching had to move to synchronous or asynchronous online instruction. In the post-Covid-19 era, institutions will, at least partially, go back to teaching in person, and blended teaching (BT) practices will conceivably become the true norm. Although BT practices have been employed and researched extensively over the past two decades, a deeper or more extensive blending of courses will still be a major switch for many teachers and students. More than ever, it is vital for instructors not just to understand how to blend but also to understand the evolution of BT practices and the choices made to arrive at sustainable practices that positively impact the learning experience. In this article, the authors aim to elaborate on the contexts which stimulate or provide a catalyst for the use and subsequent growth of sustainable BT practices in HE. A mixed approach of inductive and deductive thematic analysis is used to analyze 26 interviews of instructors, considered either as pioneers or experienced BT adopters in six HE institutions across Europe (Belgium, Denmark, Finland, Ireland, Netherlands, UK). This preliminary analysis revealed that the identified over-arching themes, the drivers and enablers that promote BT, are dynamic in nature and vary in diverse contexts. This study can give insights into BT adoption and help instructors and institutions improve planning or (re)design of courses into successful and sustainable BT practices.
Tsai, Y. S., Whitelock-Wainwright, A., & Gašević, D. (2020, March). The privacy paradox and its implications for learning analytics. In the 10th International Learning Analytics & Knowledge Conference, pages 230–239. ACM. (Author version)
In this paper, we explore student expectations of privacy issues related to learning analytics and identify gaps between what students desire and what they expect to happen or choose to do in reality when it comes to privacy protection. An investigation was carried out in a UK higher education institution using a survey (N=674) and six focus groups (26 students). The study highlight a number of key implications for learning analytics research and practice: (1) purpose, access, and anonymity are key benchmarks of ethics and privacy integrity; (2) transparency and communication are key levers for learning analytics adoption; and (3) information asymmetry can impede active participation of students in learning analytics
Falcão, T. P., Mello, R. F., Rodrigues, R. L., Diniz, J. R. B., Tsai, Y. S., & Gašević, D. (2020, March). (2020). Perceptions and expectation about learning analytics from a Brazilian higher education institution. In the 10th International Learning Analytics & Knowledge Conference, pages 240–249. ACM. (Author version)
There is a lacuna in research on stakeholders’ expectations from LA outside the Global North. This paper reports on the findings of the application of interviews and focus groups, based on the SHEILA framework, with students and teaching staff from a Brazilian public university, to investigate their perceptions of the potential benefits and risks of using LA in higher education in the country. Findings indicate that there is a high interest in using LA for improving the learning experience, in particular, being able to provide personalised feedback, to adapt teaching practices to students’ needs, and to make evidence-based pedagogical decisions. From the analysis of these perspectives, we point to opportunities for using LA in Brazilian higher education.
Whitelock-Wainwright, A., Tsai, Y. S., Lyons, K., Kaliff, S., Bryant, M., Ryan, K., & Gašević, D. (2020, March). Disciplinary differences in blended learning design: A network analytic study. In the 10th International Learning Analytics & Knowledge Conference, pages 579–588. ACM. (Author version)
Learning design research has predominately relied upon survey- and interview-based methodologies, both of which are subject to limitations of social desirability and recall. An alternative approach is offered in this manuscript, whereby physical and online learning activity data is analysed using Epistemic Network Analysis. Using a sample of 6,040 course offerings from 10 faculties across a four year period (2016-2019), the utility of networks to understand learning design is illustrated. Specifically, through the adoption of a network analytic approach, the following was found: universities are clearly committed to blended learning, but there are considerable differences both between and within disciplines.
Scheffel, M., Tsai, Y. S., Gašević, D., & Drachsler, H. (2019, September). Policy matters: Expert recommendations for learning analytics policy. In Transforming Learning with Meaningful Technologies. EC-TEL 2019., pages 510–524. Springer, Cham. (Author version)
This paper presents a mix-method study using a group concept mapping (GCM) approach that was conducted with learning analytics experts to explore essential features of LA policy in higher education in contribution the development of the framework. The study identified six clusters of features that an LA policy should include, provided ratings based on ease of implementation and importance for each of the six themes, and offered suggestions to higher education institutions how they can proceed with the development of LA policies.
Tsai, Y. S., Moreno-Marcos, P. M., Tammets, K., Kollom, K., & Gašević, D. (2018, March). SHEILA policy framework: informing institutional strategies and policy processes of learning analytics. In Proceedings of the 8th International Learning Analytics & Knowledge Conference, pages 320–329. ACM. (Best paper award runner-up). (Author version)
This paper introduces a learning analytics policy development framework developed by a cross-European research project team – SHEILA (Supporting Higher Education to Integrate Learning Analytics), based on interviews with 78 senior managers from 51 European higher education institutions across 16 countries. The framework was developed using the RAPID Outcome Mapping Approach (ROMA), which is designed to develop effective strategies and evidence-based policy in complex environments. This paper presents three case studies to illustrate the development process of the SHEILA policy framework, which can be used to inform strategic planning and policy processes in real world environments, particularly for large-scale implementation in higher education contexts.
Tsai, Y. S., & Gasevic, D. (2017, March). Learning analytics in higher education—challenges and policies: a review of eight learning analytics policies. In Proceedings of the 7th International Learning Analytics & Knowledge Conference, pages 233–242. ACM. (Author version)
This paper presents the results of a review of eight policies for learning analytics of relevance for higher education, and discusses how these policies have tried to address prominent challenges in the adoption of learning analytics, as identified in the literature. The results show that more considerations need to be given to establishing communication channels among stakeholders and adopting pedagogy-based approaches to learning analytics. It also reveals the shortage of guidance for developing data literacy among end-users and evaluating the progress and impact of learn- ing analytics. Moreover, the review highlights the need to establish formalised guidelines to monitor the soundness, effectiveness, and legitimacy of learning analytics. As interest in learning analytics among higher education institutions continues to grow, this review will provide insights into policy and strategic planning for the adoption of learning analytics.
Book chapters
Tsai, Y. S. & Martinez-Maldonado, R. (2022). Human-centered Approaches to Data-informed Feedback. In Charles Lang, George Siemens, Alyssa Friend Wise, Dragan Gašević, and Agathe Merceron (Eds.), Handbook of Learning Analytics (2nd. ed.), chapter 21, pages 213-222. SoLAR, Vancouver, BC. (open access).
Learning analytics seeks to support and enhance learning through data-informed feedback practices. As learning analytics emphasizes an iterative loop from learner to data, metrics, and interventions, it is imperative that both teachers and learners play active roles in this process and contribute to the design and evaluation of enabling technologies. A key question that concerns us is: How can learning analytics tools enhance learners’ agency in the feedback process? We argue that the design and deployment of learning analytics need to recognize feedback as a dialogic process. In doing so, we emphasize that effective feedback is not just about providing information relevant to learning, but also about the practices of the people who carry out evaluations and produce or interpret information based on such evaluations. A human-centered approach is thus critical to the effectiveness of data-informed feedback. In this chapter we discuss key elements of feedback, current approaches to data-informed feedback and associated challenges; and propose a human-centered approach which facilitates collaborative learning and continuous learning
among a network of actors and highlights the importance of developing data-informed feedback literacy among learners.
Scheffel, M., Tsai, Y. S., Gašević, D. & Drachsler, H. (2022). Learning Analytics Policies. In Charles Lang, George Siemens, Alyssa Friend Wise, Dragan Gašević, and Agathe Merceron (Eds.), Handbook of Learning Analytics (2nd. ed.), chapter 23, pages 231-239. SoLAR, Vancouver, BC. (open access).
More and more higher education institutions have been making use of learning analytics in the last few years. But despite an increased funding and more research in the learning analytics domain, there is still a lack of systematic and large-scale implementations of learning analytics. In order to improve learning analytics adoption and to establish it sustainably, higher education institutions need to align learning analytics-related activities with their goals and visions. Their making us of data requires a set of guidelines and principles, i.e. a policy, that fits their context and speaks to all involved stakeholders. Only then can the effective and responsible use of learning analytics be ensured and will higher education institutions be truly able to establish learning analytics in a sustainable way.
Tsai, Y. S. (2021). The role of comic books in literacy education in Taiwan. In Su Li Chong, editor, Charting an Asian Trajectory for literacy education: Connecting past, present and future literacies, chapter 8, pages136–151. Routledge, London. (Author version).
Children in Taiwan actively seek out manga to enjoy the pleasure of reading. However, the social stigma has resulted in fear of potential harm to child development and an insufficient understanding of the complexity and literary values of manga and comics in general. In this chapter, the author traces the historical influence on comics in Taiwan from the creation of comics to the formation of a reading culture. Drawing on an example of the texts recommended by a governmental reading campaign, the author provides a critical analysis and practical suggestions for the use of comic books in the classroom.
Ieshima, A., Tsai, Y. S., Allison, B., & Yamamoto, T. (2021). Positive use of visual media to understand and prevent bullying: The popularity and possibility of manga. In Toda Yuichi and Oh Insoo, editors, Tackling Cyberbullying and Related Problems: Innovative Usage of Games, Apps and Manga, chapter 4, pages 46–64. Routledge, London, New York, NY. (Author version).
This chapter focuses on the impact of manga on children. Visual media such as manga, anime, and games are very popular among children not only in Japan, but also in other countries. Although such pop cultures have achieved widespread popularity worldwide, little is known about their impact on children. In particular, positive aspects are not well discussed. Therefore, it is necessary to investigate the significance of their popularity and possible impact on children. This chapter discusses the following three points: 1) the reason children are devoted to manga, 2) impact of manga on children, and 3) positive use of manga to prevent traditional/cyber bullying and other Internet-related problems. Although the most popular view of manga tends to be negative regarding the impact on child readers, we challenge this view by investigating the potential of using manga to positively influence children’s well-being. This chapter discusses the recent history of manga, its current situation, and the possibility of introducing a new usage of manga to positively impact children.
Hilliger, I., Pérez-Sanagustín, M., Pérez-Álvarez, R., Henríquez, V., Guerra, J., Zuñiga-Prieto, M. Á., … & De Laet, T. (2020). Leadership and maturity: How do they affect learning analytics adoption in Latin America. In Dirk Ifenthaler and David Gibson, editors, Adoption of Data Analytics in Higher Education Learning and Teaching, pages305–326. Springer, New York. (Author version).
Learning Analytics (LA) can provide useful information for addressing educational needs in Latin American universities, such as reducing program quality disparities and student dropout rates. Some researchers have suggested to build capacity in this region for institutional adoption of LA tools. Yet, there is still a long way to move from experimentation to actual integration of LA tools into institutional processes. With the objective of understanding how we could facilitate LA adoption in Latin American contexts, we present the cases of four Latin American universities adapting LA tools to meet institutional needs. Two questionnaires with open-ended questions were used to identify similarities and differences among the four cases in terms of two dimensions: 1) leadership processes to involve diverse stakeholders in the adoption of LA tools, and 2) organizational maturity to analyze and act upon educational data. Findings indicate that leadership processes for LA adoption that engage middle-managers, such as deans and directors of undergraduate studies, facilitated the involvement of intended users to receive feedback on the design, and of senior managers to allocate resources for scaling up the LA initiative. Besides, a greater organizational maturity facilitated the incorporation of the LA tool into an existing academic process at a department or institutional level. Future work might explore how leadership processes and organizational maturity evolve in other Latin American universities, in order to provide guidelines and recommendations for scaling LA adoption in different contexts.
Tsai, Y. S. (2016). Looking through the enemy’s eyes: point-of-view editing and character identification in manga Naruto. In Kathrin Muschalik and Florian Fiddrich, editors, Sequential Art: Interdisciplinary Approaches to the Graphic Novel, pages 55–63. Brill, Leiden. First published by Inter-Disciplinary Press in 2016. (Author version).
Various cinematic traditions have influenced manga, thanks to the ‘god of manga,’Osamu Tezuka, who brought this revolutionary change to the creation of manga in Japan. Cinematic views give artists the freedom to play with angles, perspectives, and distances of shots as if they were holding a camera. They serve to direct readers’ attention to specific details in order to achieve the purposes of a narrative. This chapter explores how manga artists employ point-of-view editing to engage readers by broadening the range of identification with characters. The reader is positioned in a double structure of the viewer (through whom they see) and the viewed (the one under the reader’s gaze). Both agents invite the reader to join their experiences in the fictional world.
Research reports
Yi-Shan Tsai, Dragan Gašević, Alexander Whitelock-Wainwright, Pedro José Muñoz Merino, Pedro Manuel Moreno-Marcos, Aarón Rubio‐Fernández, Carlos Delgado Kloos, Maren Scheffel, Ioana Jivet, Hendrik Drachsler, Kairit Tammets, Adolfo Ruiz Calleja, and Kaire Kollom (2018). Supporting Higher Education to Integrate Learning Analytics: Research Report. pages 1–44.
Conference posters and workshops
Tsai, Y. S., Peffer, M., Shibani, A., Hilliger, Chen, B., Fan, Y., Kaliisa, R., Dowell, N., and Knight, S. (2022, March). Writing for Publication: Engaging Your Audience. In Companion Proceedings of the 12th International Learning Analytics & Knowledge Conference, pages 169-172. Society for Learning Analytics Research. Workshop.
Tsai, Y. S., Mello, R. F., Pontual, T., Burke, M. & Gašević, D. (2021, April). Dichotomous views of automation in feedback practice. In Companion Proceedings of the 11th International Learning Analytics & Knowledge Conference, pages 52-54. Society for Learning Analytics Research. Poster. (View poster)
Echeverria, V., Lawrence, L., Tsai, Y. S., Singh, S.,Fernandez-Nieto, G. M., Martinez-Maldonado, R. (2021, April). A Tutorial on Data Storytelling for Learning Analytics Dashboards. In Companion Proceedings of the 11th International Learning Analytics & Knowledge Conference, pages 421-424. Society for Learning Analytics Research. Workshop.
Tsai, Y. S., Kovanović, V., & Gašević, D. (2019, January). Learning analytics adoption–approaches and maturity. In Companion Proceedings of the 9th International Learning Analytics & Knowledge Conference, pages 147–148. Society for Learning Analytics Research. Poster. (View poster)
Tsai, Y. S., Scheffel, M. , & Gašević, D. (2018, May). Developing an evidence-based institutional LA policy. In Companion Proceedings of the 8th International Learning Analytics & Knowledge Conference, pages 455–458. Society for Learning Analytics Research. Poster. (Best poster award). (View poster)
Tsai, Y. S., Scheffel, M. , & Gašević, D. (2018, September). Enabling systematic adoption of learning analytics through a policy framework. In Proceedings of the 13th European Conference on Technology Enhanced Learning, pages 556–560. Springer, Cham. Workshop.
Tsai, Y. S., Gasevic, D., Muñoz-Merino, P. J., & Dawson, S. (2017, March). LA policy: developing an institutional policy for learning analytics using the RAPID outcome mapping approach. In Companion Proceedings of the 7th International Learning Analytics & Knowledge Conference, pages 494–495. Society for Learning Analytics Research. Workshop.
PhD thesis
Tsai, Y. S. (2015). Young British readers’ engagement with manga. PhD thesis, University of Cambridge.
This thesis presents young British readers’ engagement with manga regarding literary, aesthetic, social, and cultural dimensions. The study explores young readers’ points of views of their reading preference – manga. I investigated how children interpreted manga, with respect to the artistic techniques, the embedded ideologies, and the cultural elements therein. I also looked into children’s participation in manga fandom and its social meanings. This study involved 16 participants from two schools, aged between 10 and 15, with genders represented equally. The findings show that the attraction of participants to manga includes at least five dimensions. First, manga is a visually rich text, which not only had great power in rendering vicarious experiences to the students, but also allowed the struggling students to grasp the meanings of the text better. Second, both the verbal and the visual storytelling were characterised as fragmentary, which inspired the students’ imagination to join the creation of the story. Third, manga provided a temporary shelter where the participants could forget a stressful and frustrating reality. In addition, they felt that they gained renewed hope, refreshed energy, and insights to face potential challenges and difficulties in their lives. Fourth, the elements of Japaneseness and otherness made manga reading a rich experience of an exotic culture. Fifth, manga afforded collective pleasures in fan communities where the students could express their passion and gained a sense of identity.
