A5091718256- Online Learning and Analytics
- Online and Blended Learning
- E-Learning and Knowledge Management
- Evaluation of Teaching Practices
- Innovative Teaching and Learning Methods
- Educational Innovations and Technology
- Artificial Intelligence in Healthcare and Education
- COVID-19 and Mental Health
- Text Readability and Simplification
- Business Process Modeling and Analysis
- Educational Strategies and Epistemologies
- Communication in Education and Healthcare
- Big Data and Business Intelligence
- Topic Modeling
- Health Policy Implementation Science
- Privacy-Preserving Technologies in Data
- Learning Styles and Cognitive Differences
- Customer Service Quality and Loyalty
- Primary Care and Health Outcomes
- Patient Satisfaction in Healthcare
Monash University
2019-2024
Australian Regenerative Medicine Institute
2021
University of Liverpool
2017-2019
Online learning is currently adopted by educational institutions worldwide to provide students with ongoing education during the COVID-19 pandemic. Even though online research has been advancing in uncovering student experiences various settings (i.e., tertiary, adult, and professional education), very little progress achieved understanding experience of K-12 population, especially when narrowed down different school-year segments primary secondary school students). This study explores how...
The recent focus on learning analytics (LA) to analyze temporal dimensions of holds the promise providing insights into latent constructs, such as strategy, self-regulated (SRL), and metacognition. These methods seek provide an enriched view learner behaviors beyond scope commonly used correlational or cross-sectional methods. In this article, we present a methodological sequence techniques that comprises: 1) strategic clustering types; 2) use microlevel processing transform raw trace data...
Learning analytics promises to support adaptive learning in higher education. However, the associated issues around privacy protection, especially their implications for students as data subjects, has been a hurdle wide-scale adoption. In light of this, we set out understand student expectations related and identify gaps between what desire they expect happen or choose do reality when it comes protection. To this end, an investigation was carried UK education institution using survey (N=674)...
Abstract Student engagement within the development of learning analytics services in Higher Education is an important challenge to address. Despite calls for greater inclusion stakeholders, there still remains only a small number investigations into students’ beliefs and expectations towards services. Therefore, this paper presents descriptive instrument measure student (ideal predicted) The scales used are grounded theoretical framework expectations, specifically ideal predicted...
Student engagement is often considered an overarching construct in educational research and practice. Though frequently employed the learning analytics literature, has been subjected to a variety of interpretations there little consensus regarding very definition construct. This raises grave concerns with regards validity: namely, do these varied metrics measure same thing? To address such concerns, this paper proposes, quantifies, validates model which both grounded theoretical literature...
For service implementations to be widely adopted, it is necessary for the expectations of key stakeholders considered. Failure do so may lead services reflecting ideological gaps, which will inadvertently create dissatisfaction among its users. Learning analytics research has begun recognise importance understanding student perspective towards that could potentially offered; however, engagement remains low. Furthermore, there been no attempt explore whether students can segmented into...
Abstract Background Learning Analytics (LA) is an emerging field concerned with measuring, collecting, and analysing data about learners their contexts to gain insights into learning processes. As the technology of evolving, many systems are being implemented. In this context, it essential understand stakeholders' expectations LA across Higher Education Institutions (HEIs) for large‐scale implementations that take needs account. Objectives This study aims contribute knowledge individual...
Abstract To assist higher education institutions in meeting the challenge of limited student engagement implementation Learning Analytics services, Questionnaire for Student Expectations (SELAQ) was developed. This instrument contains 12 items, which are explained by a purported two‐factor structure “Ethical and Privacy Expectations” “Service Feature Expectations.” As it stands, however, SELAQ has only been validated with students from UK university, is problematic on account interest...
Abstract In Latin American universities, Learning Analytics (LA) has been perceived as a promising opportunity to leverage data meet the needs of diverse student cohort. Although universities have collecting educational for years, adoption LA in this region is still limited due lack expertise and policies processing using data. order get better picture how existing data‐related practices might affect incorporation institutions, we conducted mixed methods study four (two Chilean two...
The use of learning trace data together with various analytical methods has proven successful in detecting patterns behaviour, identifying student profiles, and clustering resources. However, interpretation the findings is often difficult uncertain due to a lack contextual (e.g., on motivation, emotion or curriculum design). In this study we explored integration self-reports about cognitive load self-efficacy into process collection relevant students' perceptions as traces. Our objective was...
The adoption of learning analytics (LA) in complex educational systems is woven into sociocultural and technical challenges that have induced distrust data difficulties scaling LA. This paper presents a study investigated areas threats to trustworthy LA through series consultations with teaching staff students at large UK university. Surveys focus groups were conducted explore participant expectations observed broadly attributed three areas: the subjective nature numbers, fear power...
In online courses, discussion forums play a key role in enhancing student interaction with peers and instructors. Due to large enrolment sizes, instructors often struggle respond students timely manner. To address this problem, both traditional machine learning (ML) (e.g., Random Forest) deep (DL) approaches have been applied classify educational forum posts those that required urgent responses versus did not). However, there lacks an in-depth comparison between these two kinds of...
Quality assurance in any organization is important for ensuring that service users are satisfied with the offered. For higher education institutes, use of quality measures allows ideological gaps to be both identified and resolved. The learning analytic community, however, has rarely addressed concept quality. A potential outcome this provision a analytics only meets expectations certain stakeholders (e.g., managers), whilst overlooking those who most students). In order resolve issue, we...
Abstract Self‐regulated learning (SRL) is an essential skill to achieve one's goals. This particularly true for online environments (OLEs) where the support system often limited compared a traditional classroom setting. Likewise, existing research has found that learners struggle adapt their behaviour self‐regulatory demands of OLEs. Even so, SRL analysis tools have utility real‐time or individualised learner's strategy during study session. Accordingly, we explore reinforcement based...
Learning design research has predominately relied upon survey- and interview-based methodologies, both of which are subject to limitations social desirability recall. An alternative approach is offered in this manuscript, whereby physical online learning activity data analysed using Epistemic Network Analysis. Using a sample 6,040 course offerings from 10 faculties across four year period (2016--2019), the utility networks understand illustrated. Specifically, through adoption network...
Student ratings are the most used and influential measure of performance in Higher Education, an integral component formative summative decision making. This may be particularly relevant relatively new online courses, where pedagogical model is still developing. However, student face strong controversy, some remarkable challenges –one which stems from fact that not all students provide ratings. Nonresponse bias, or lack representativeness providers ratings, has been measured discussed...