ORCID Profile
0000-0003-2435-2193
Current Organisation
University of South Australia
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Educational Technology and Computing | Specialist Studies in Education | Learning Sciences
Teaching and Instruction Technologies | Learner and Learning Processes | Application Software Packages (excl. Computer Games) |
Publisher: Australasian Society for Computers in Learning in Tertiary Education
Date: 29-09-2011
DOI: 10.14742/AJET.921
Abstract: span Despite the burgeoning rhetoric from political, social and educational commentators regarding creativity and learning and teaching, there is a paucity of scalable and measurable ex les of creativity-centric pedagogical practice. This paper makes an argument for the application of social network visualisations to inform and support creativity-enabling pedagogical practice. This paper first describes social networks and how they relate to creative capacities and learning as a social process. It then provides an initial case study of how social network analysis may be meaningfully applied to evaluate students' learning networks and creative capacities, and elaborates on how such an evaluative resource can allow educators to design and implement creativity-enabling pedagogical practice. In so doing, this paper contributes conceptual, methodological and empirical advances that can take learning and teaching for creativity, particularly in higher education, beyond rhetoric towards more observable and measurable mainstream pedagogical practice. /span
Publisher: Elsevier BV
Date: 04-2018
Publisher: Springer New York
Date: 2012
Publisher: ACM
Date: 13-03-2023
Publisher: Auckland University of Technology (AUT) Library
Date: 08-02-2022
Abstract: Learning is a social experience and having meaningful connections with peers and instructors is important for student learning. The interpersonal relationships between students and their instructor can positively influence students’ well-being, motivation and self-efficacy (Aguilera-Hermida, 2020 Almendingen et al., 2021 Gillis & Krull, 2020 Kim & Sax, 2009 Marković et al., 2021 Parpala et al., 2021 Pitsick, 2018). Creating productive interpersonal relationships with peers contributes to students’ beliefs of being supported, respected, and valued, and increases the likelihood of students asking their peers for help (Mäkitalo-Siegl & Fischer, 2011). When students feel connected to their peers they are more likely to engage with their peers in ways that support their learning and deepen their knowledge as a result (Shim et al., 2013). Interaction with instructors can also positively influence learning outcomes and student well-being (Pitsick, 2018), and instructors can be a valuable source of help and guidance (Ryan et al., 2001). However, during the COVID-19 pandemic and the shift to emergency remote teaching and learning, students’ relationship with peers was significantly impacted (Motz et al., 2022) and forcing peer-to-peer interaction through mandating camera feeds on during live synchronous video classes disproportionately affected students from disadvantaged backgrounds and those experiencing anxiety or depression (Castelli & Sarvary, 2021). As students were adapting to learn during the pandemic, they increased their reliance on their instructor and highly ranked instructor engagement as a factor that positively influenced their motivation (Nguyen, 2021). As motivation increases, so does self-efficacy, and when students feel supported, engaged, connected and valued by their peers and instructors, they are more likely to be successful students (Zepke, 2018). This study examines students’ experiences in using technology to connect with peers and their instructors during the COVID-19 pandemic when learning remotely. The research inquiry focusses on the second-year cohort as prior research has revealed that this group of learners tend to struggle with their learning (Kyndt et al., 2017 Milsom, 2015 Milsom & Yorke, 2015 Southgate et al., 2014 Virtue et al., 2017 Webb & Cotton, 2019) and experience higher levels of anxiety and depression compared to students in other years of university study prior to the COVID 19 pandemic (Liu et al., 2019). To examine their experience in peer-to-peer networks and their interactions with instructors for help seeking, interviews were undertaken at a large metropolitan Australian University in 2021 with 26 second-year students across different disciplines who had experienced emergency remote teaching in their first and second year of study. The findings reveal that students resist using the discussion board in the Learning Management System because of perceptions of exposure and embarrassment in asking questions when they feel they are expected to know the answer. Students report that synchronous video classes using technology such as Zoom, increase feelings of isolation and they reach out to their peers via social media technology instead. Students are intentional in their choice of technology in connecting with peers, however in the absence of physical connections, there remains a gap in productive engagement with peers. The findings show that second-year students are reluctant to reach out to their instructor when technology is their only mode of interaction, and students report that they would have been more likely to ask for help during a face-to-face class.
Publisher: ACM Press
Date: 2016
Publisher: Informa UK Limited
Date: 14-05-2018
Publisher: IEEE
Date: 2014
Publisher: IEEE
Date: 2013
Publisher: Wiley
Date: 16-07-2019
DOI: 10.1111/BJET.12846
Publisher: ACM
Date: 04-03-2019
Publisher: ACM
Date: 04-03-2019
Publisher: ACM
Date: 13-03-2017
Publisher: Elsevier BV
Date: 02-2017
Publisher: Australasian Society for Computers in Learning in Tertiary Education
Date: 22-11-2006
DOI: 10.14742/AJET.1282
Abstract: blockquote Given the current ersity of communication tools at an educator's disposal, what role (if any) does the discussion forum play in the development of a strong sense of community among students? This study sought to investigate the relationship between discussion forum interaction and perceived student sense of community. The results of the study demonstrate that while mere quantity of discussion forum postings is not an indicator of community development, a significant relationship is observed when contributions are codified into the various discussion interaction types (learner - learner learner - content system). An implication emerging from these findings is the ability for the institution to implement evaluative measures to gauge levels of student sense of community in a just in time environment. As discussion interactions are automatically captured and reported, the data provides an indication of the degree of community developing among the student population at a specific snapshot in time. As multiple snapshots provide an ongoing indicator of community development, practitioners have the capacity to develop intervention activities designed to promote further peer to peer discussion and therefore, facilitate the development of a strong sense of community. /blockquote
Publisher: BRILL
Date: 2008
Publisher: Informa UK Limited
Date: 02-10-2017
Publisher: Elsevier BV
Date: 04-2019
Publisher: Elsevier BV
Date: 02-2010
Publisher: Inderscience Publishers
Date: 2013
Publisher: Routledge
Date: 19-11-2015
Publisher: Australasian Society for Computers in Learning in Tertiary Education
Date: 16-03-2015
DOI: 10.14742/AJET.1448
Abstract: class="AJET-Abstract" This study explored the concept of social capital in higher education contexts by investigating student discussion forum activity and academic performance. To address these aims online discussion forum logs, student marks and teaching delivery method (blended or fully online) data were extracted from the universities learning management system (LMS). Student social network centrality measures were then calculated from the course discussion activity and correlated against student academic performance for each delivery mode. Drawing on social capital and social network theories the analyses identified that in comparison to low performing students the high-performing group held more central positions in their networks and tended to establish dense social connections with students of a similar academic ability. It was also observed that the relationships formed in blended teaching units were of a greater intensity and reciprocity than those established in fully online teaching units indicating a higher level of social capital was reached. This difference in the amount of available social capital between the two teaching modes suggests that students in blended units have comparatively greater access to resources embedded within the network, which in turn can be mobilised to assist them in their academic endeavours.
Publisher: IGI Global
Date: 2011
DOI: 10.4018/978-1-60960-519-3.CH005
Abstract: In this chapter, social relationship patterns associated with outstanding innovation are described and explored. In doing so, the chapter draws upon the findings of 16 in-depth interviews with award-winning Australian innovators from science & technology and the creative industries. The interviews covered topics relating to various influences on in idual innovation capacity and career development. For all of the participants, innovation was a highly social process. Although each had been recognised in idually for their innovative success, none worked in isolation. The ability to generate innovative outcomes was grounded in certain types of interaction and collaboration. The chapter outlines the distinctive features of the social relationships which seem to be important to innovation, and ask which ‘social network capabilities’ might underlie the ability to create an optimal pattern of interpersonal relationships. The implications of these findings for universities play a key role in the development of nascent innovators.
Publisher: ACM Press
Date: 2016
Publisher: Emerald
Date: 02-2006
DOI: 10.1108/09513540610646118
Abstract: This paper demonstrates the need for the higher education sector to develop and implement scaleable, quantitative measures that evaluate community and establish organisational benchmarks in order to guide the development of future practices designed to enhance the student learning experience. Literature regarding contemporary Australian higher education policy and community development is critiqued to illustrate the need for universities to adopt scaleable quantitative measures to evaluate stated strategic imperatives and establish organisational benchmarks. The integration of organisational benchmarks guides the implementation of future practices designed to enhance the student learning experience. A current active exemplar methodology is discussed to demonstrate applicability to both higher education administrators and teaching staff across the various organisation levels. While universities are promoting and investing in the concept of community to enhance the student learning experience there are as yet, limited scaleable evaluative measures and performance indicators to guide practitioners. This paper proposes an effective measurement tool to benchmark current pedagogical performance standards and monitor the progress and achievement of future implemented practices designed to enhance the sense of community experienced by the student cohort. This paper identifies and addresses the current absence of effective scaleable evaluative measures to assess the achievement of stated strategic imperatives implemented as a consequence of reducing government financial support, increasing accountability, and increasing student expectations as result of educational consumerism.
Publisher: Elsevier BV
Date: 04-2021
Publisher: IEEE
Date: 2015
Publisher: ACM
Date: 27-02-2011
Publisher: Wiley
Date: 06-11-2017
DOI: 10.1111/BJET.12592
Publisher: Athabasca University Press
Date: 11-07-2018
DOI: 10.19173/IRRODL.V19I3.3370
Abstract: The capacity to foster interpersonal interactions in massive open online courses (MOOCs) has frequently been contested, particularly when learner interactions are limited to MOOC forums. The establishment of social presence—a perceived sense of somebody being present and “real”—is among the strategies to tackle the challenges of online learning and could be applied in MOOCs. Thus far, social presence in MOOCs has been under-researched. Studies that previously examined social presence in MOOCs did not account for the peculiar nature of open online learning. In contrast to the existing work, this study seeks to understand how learners perceive social presence, and the different nuances of social presence in erse MOOC populations. In particular, we compare perceptions of social presence across the groups of learners with different patterns of forum participation in three edX MOOCs. The findings reveal substantial differences in how learners with varying forum activity perceive social presence. Perceptions of social presence also differed in courses with the varying volume of forum interaction and duration. Finally, learners with sustained forum activity generally reported higher social presence scores that included low affectivity and strong group cohesion perceptions. With this in mind, this study is significant because of the insights into brings to the current body of knowledge around social presence in MOOCs. The study’s findings also raise questions about the effectiveness of transferring existing socio-constructivist constructs into the MOOC contexts.
Publisher: Emerald
Date: 23-02-2010
DOI: 10.1108/09513541011020936
Abstract: This paper aims to examine how effective higher education institutions have been in harnessing the data capture mechanisms from their student information systems, learning management systems and communication tools for improving the student learning experience and informing practitioners of the achievement of specific learning outcomes. The paper seeks to argue that the future of analytics in higher education lies in the development of more comprehensive and integrated systems to value add to the student learning experience. Literature regarding the trend for greater accountability in higher education is reviewed in terms of its implications for greater “user driven” direction. In addition, IT usage within higher education and contemporary usage of data captured from various higher education systems is examined and compared to common commercial applications to suggest how higher education management and teachers can gain greater understanding of the student cohort and personalise and enhance the learning experience much as commercial entities have done for their client base. A way forward for higher education is proposed. If the multiple means that students engage with university systems are considered, it is possible to track in idual activity throughout the entire student life cycle – from initial admission, through course progression and finally graduation and employment transitions. The combined data captured by various systems builds a detailed picture of the activities students, instructors, service areas and the institution as a whole undertake and can be used to improve relevance, efficiency and effectiveness in a higher education institution. The paper outlines how academic analytics can be used to better inform institutions about their students learning support needs. The paper provides ex les of IT automation that may allow for student user‐information to be translated into a personalised and semi‐automated support system for students.
Publisher: ACM
Date: 27-02-2011
Publisher: Springer International Publishing
Date: 2022
Publisher: ACM
Date: 13-03-2017
Publisher: Society for Learning Analytics Research
Date: 18-02-2015
Abstract: With the widespread adoption of Learning Management Systems (LMS) and other learning technology, large amounts of data – commonly known as trace data – are being recorded and are readily accessible to educational researchers. Among different uses of trace data, it has been extensively used to calculate time that students spent on different learning activities – commonly referred to as student time-on-task. Extracted time-on-task measures are then used to build predictive models of student learning in order to understand and improve learning processes. While time-on-task measures have been extensively used in Learning Analytics research, the details of their estimation are rarely described and the consequences that this process entails are not fully examined.This paper presents findings from two experiments that looked at the different time-on-task estimation methods and how they influence the final research findings. Based on modeling different student performance measures with popular statistical methods in two datasets (one online and one blended), our findings indicate that time-on-task estimation methods play an important role in shaping the final study results. This is particularly true for online setting where the amount of interaction with LMS is typically higher. The primary goal of this paper is to raise awareness and initiate a debate on the important issue of time-on-task estimation within a broader learning analytics community. Finally, the paper provides an overview of commonly adopted time-on-task estimation methods in educational and related research fields.
Publisher: ACM
Date: 13-03-2023
Publisher: ACM Press
Date: 2016
Publisher: ACM
Date: 29-04-2012
Publisher: ACM
Date: 04-03-2019
Publisher: ACM
Date: 29-04-2012
Publisher: Elsevier BV
Date: 07-2006
Publisher: Elsevier BV
Date: 07-2019
Publisher: ACM Press
Date: 2016
Publisher: ACM Press
Date: 2016
Publisher: Springer Science and Business Media LLC
Date: 21-12-2015
Publisher: Australasian Society for Computers in Learning in Tertiary Education
Date: 28-03-2018
DOI: 10.14742/AJET.3207
Abstract: The rapid growth of blended and online learning models in higher education has resulted in a parallel increase in the use of audio-visual resources among students and teachers. Despite the heavy adoption of video resources, there have been few studies investigating their effect on learning processes and even less so in the context of academic development. This paper uses learning analytic techniques to examine how academic teaching staff engage with a set of prescribed videos and video annotations in a professional development course. The data was collected from two offerings of the course at a large research-intensive university in Australia. The data was used to identify patterns of activity and transition states as users engaged with the course videos and video annotations. Latent class analysis and hidden Markov models were used to characterise the evolution of engagement throughout the course. The results provide a detailed description of the evolution of learner engagement that can be readily translated into action aimed at increasing the quality of the learning experience.
Publisher: Athabasca University Press
Date: 19-06-2015
DOI: 10.19173/IRRODL.V16I3.2170
Abstract: Distributed Massive Open Online Courses (MOOCs) are based on the premise that online learning occurs through a network of interconnected learners. The teachers’ role in distributed courses extends to forming such a network by facilitating communication that connects learners and their separate personal learning environments scattered around the Internet. The study reported in this paper examined who fulfilled such an influential role in a particular distributed MOOC – a connectivist course (cMOOC) offered in 2011. Social network analysis was conducted over a socio-technical network of the Twitter-based course interactions, comprising both human course participants and hashtags where the latter represented technological affordances for scaling course communication. The results of the week-by-week analysis of the network of interactions suggest that the teaching function becomes distributed among influential actors in the network. As the course progressed, both human and technological actors comprising the network subsumed the teaching functions, and exerted influence over the network formation. Regardless, the official course facilitators preserved a high level of influence over the flow of information in the investigated cMOOC.
Publisher: ACM
Date: 08-04-2013
Publisher: American Educational Research Association (AERA)
Date: 14-11-2017
Abstract: Despite a surge of empirical work on student participation in online learning environments, the causal links between the learning-related factors and processes with the desired learning outcomes remain unexplored. This study presents a systematic literature review of approaches to model learning in Massive Open Online Courses offering an analysis of learning-related constructs used in the prediction and measurement of student engagement and learning outcome. Based on our literature review, we identify current gaps in the research, including a lack of solid frameworks to explain learning in open online setting. Finally, we put forward a novel framework suitable for open online contexts based on a well-established model of student engagement. Our model is intended to guide future work studying the association between contextual factors (i.e., demographic, classroom, and in idual needs), student engagement (i.e., academic, behavioral, cognitive, and affective engagement metrics), and learning outcomes (i.e., academic, social, and affective). The proposed model affords further interstudy comparisons as well as comparative studies with more traditional education models.
Publisher: Association for Computational Linguistics
Date: 2019
DOI: 10.18653/V1/W19-3505
Publisher: Wiley
Date: 07-06-2023
DOI: 10.1111/BJET.13343
Publisher: Informa UK Limited
Date: 03-07-2019
Publisher: Elsevier BV
Date: 04-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2019
Publisher: ACM
Date: 24-03-2014
Publisher: ACM
Date: 12-04-2021
Publisher: International Society for the Scholarship of Teaching and Learning
Date: 09-2014
Publisher: Elsevier BV
Date: 03-2022
Publisher: Elsevier BV
Date: 2021
Publisher: Springer US
Date: 2009
Publisher: Edward Elgar Publishing
Date: 10-06-2022
Publisher: Australasian Society for Computers in Learning in Tertiary Education
Date: 23-12-2020
DOI: 10.14742/AJET.6370
Abstract: Although technological advances have brought about new opportunities for scaling feedback to students, there remain challenges in how such feedback is presented and interpreted. There is a need to better understand how students make sense of such feedback to adapt self-regulated learning processes. This study examined students’ sense-making of learning analytics–based personalised feedback across four courses. Results from a combination of thematic analysis and epistemic network analysis show an association between student perceptions of their personalised feedback and how these map to subsequent self-described self-regulated learning processes. Most notably, the results indicate that personalised feedback, elaborated by personal messages from course instructors, helps students refine or strengthen important forethought processes of goal-setting, as well as to reduce procrastination. The results highlight the need for instructors to increase the dialogic element in personalised feedback in order to reduce defensive reactions from students who hold to their own learning strategies. This approach may prompt reflection on the suitability of students’ current learning strategies and achievement of associated learning goals. Implications for practice or policy: Personalised feedback based on learning analytics should be informed by an understanding of students’ self-regulated learning. Instructors implementing personalised feedback should align this closely with the course curriculum. Instructors implementing personalised feedback in their courses should consider the relational element of feedback by using a positive tone. Personalised feedback can be further enhanced by increasing the dialogic element and by including more information about learning strategies.
Publisher: Springer Science and Business Media LLC
Date: 06-1996
DOI: 10.1007/BF00349244
Publisher: Springer Science and Business Media LLC
Date: 14-02-2008
Publisher: ACM
Date: 24-03-2014
Publisher: Queensland University of Technology
Date: 16-10-2023
DOI: 10.5204/SSJ.3008
Publisher: ACM
Date: 24-03-2014
Publisher: Springer Science and Business Media LLC
Date: 13-05-2016
Publisher: Informa UK Limited
Date: 27-10-2022
Publisher: Informa UK Limited
Date: 30-06-2021
Publisher: ACM
Date: 16-03-2015
Publisher: Elsevier BV
Date: 06-2019
Publisher: Elsevier BV
Date: 04-2017
Publisher: ACM Press
Date: 2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2013
DOI: 10.1109/TLT.2012.15
Publisher: Australasian Society for Computers in Learning in Tertiary Education
Date: 09-03-2011
DOI: 10.14742/AJET.979
Abstract: blockquote Notions of what it is to be knowledgeable and skilled in one's profession have evolved in recent decades. For instance, medical practitioners are expected to think critically and creatively, communicate effectively, and to be a professional and community leader. While these attributes have always been well regarded, it is only relatively recently that higher education institutions are actively incorporating these skills and attributes into student admissions criteria. In parallel, methods of instruction and course delivery have also changed over time with respect to these driving social paradigms. Today's medical schools are expected to both select and develop students in terms of these qualities through socially based pedagogical practices. This paper investigates the admissions criteria that best predict student engagement in a social learning environment and thus the related attributes such as communication, creativity, and leadership. The paper frames this investigation in the scholarship related to 21st century skills and achievement orientations. /blockquote
Publisher: Informa UK Limited
Date: 26-05-2015
Publisher: Elsevier BV
Date: 2018
Publisher: Elsevier BV
Date: 10-2020
Publisher: Elsevier BV
Date: 2019
Publisher: ACM
Date: 23-03-2020
Publisher: SAGE Publications
Date: 10-09-2013
Abstract: This introduction to the special issue on learning analytics provides an overview of the area, acknowledging the research traditions it emerges from, such as computer-supported collaborative learning, academic analytics, and educational data mining, and the way the field aims to bridge from technological innovation to learning purposes. The introduction provides ex les of areas and educational stakeholders who are served by and can benefit from learning analytics initiatives, referring throughout to the articles in this special issue.
Publisher: ACM
Date: 16-03-2015
Publisher: Society for Learning Analytics Research
Date: 05-07-2017
Abstract: The use of analytic methods for extracting learning strategies from trace data has attracted considerable attention in the literature. However, there is a paucity of research examining any association between learning strategies extracted from trace data and responses to well-established self-report instruments and performance scores. This paper focuses on the link between the learning strategies identified in the trace data and student reported approaches to learning. The paper reports on the findings of a study conducted in the scope of an undergraduate engineering course (N=144) that followed a flipped classroom design. The study found that learning strategies extracted from trace data can be interpreted in terms of deep and surface approaches to learning. The detected significant links with self-report measures are with small effect sizes for both the overall deep approach to learning scale and the deep strategy scale. However, there was no observed significance linking the surface approach to learning and surface strategy nor were there significant associations with motivation scales of approaches to learning. The significant effects on academic performance were found, and consistent with the literature that used self-report instruments showing that students who followed a deep approach to learning had a significantly higher performance.
Publisher: IEEE
Date: 2012
Publisher: Queen's University Library
Date: 09-2006
Abstract: Contemporary education institutions are increasingly investing fiscal and human resources to further develop their online infrastructure in order to enhance flexible learning options and the overall student learning experience. Coinciding with the implementation of these technologies has been the centralisation of data and the emergence of online activities that have afforded the capacity for more intimate modes of surveillance by both the institution and education practitioner. This study offers an initial investigation into the impact of such modes of surveillance on student behaviours. Both internal and external students surveyed indicated that their browsing behaviours, the range of topics discussed and the writing style of their contributions made to asynchronous discussion forums are influenced by the degree to which such activities are perceived to be surveyed by both the institution and teaching staff. The analyses deriving from this data are framed within Foucault's works on surveillance and self governance. This paper discusses the implications of this new mode of governance for learning and teaching and suggests areas of further investigations.
Publisher: Society for Learning Analytics Research (SoLAR)
Date: 05-2017
DOI: 10.18608/HLA17.014
Publisher: Wiley
Date: 13-08-2010
Publisher: Elsevier BV
Date: 2016
Publisher: ACM
Date: 07-03-2018
Publisher: Springer Science and Business Media LLC
Date: 21-06-2018
Publisher: Emerald
Date: 05-08-2019
DOI: 10.1108/IJILT-02-2019-0024
Abstract: The analysis of data collected from user interactions with educational and information technology has attracted much attention as a promising approach to advancing our understanding of the learning process. This promise motivated the emergence of the field of learning analytics and supported the education sector in moving toward data-informed strategic decision making. Yet, progress to date in embedding such data-informed processes has been limited. The purpose of this paper is to address 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? A narrative review is performed to synthesize the existing literature on learning analytics adoption in higher education. The synthesis is based on the established models for the adoption of business analytics and finding two projects performed in Australia and Europe to develop and evaluate approaches to adoption of learning analytics in higher education. 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. The paper proposed approach that can be used by senior leaders, practitioners and researchers interested in adoption of learning analytics in higher education. The proposed approach highlights the importance of the socio-technical nature of learning analytics and complexities pertinent to innovation adoption in higher education institutions.
Publisher: ACM
Date: 07-03-2018
Publisher: ACM
Date: 07-03-2018
Publisher: Routledge
Date: 05-11-2010
Publisher: Elsevier BV
Date: 12-2018
Publisher: Society for Learning Analytics Research
Date: 11-12-2018
Abstract: The learning analytics community has matured significantly over the past few years as a middle space where technology and pedagogy combine to support learning experiences. To continue to grow and connect these perspectives, research needs to move beyond the level of basic support actions. This means exploring the use of data to prove richer forms of actions, such as personalized feedback, or hybrid approaches where instructors interpret the outputs of algorithms and select an appropriate course of action. This paper proposes the following three contributions to connect data extracted from the learning experience with such personalized student support actions: 1) a student–instructor centred conceptual model connecting a representation of the student information with a basic set of rules created by instructors to deploy Personalized Learning Support Actions (PLSAs) 2) a software architecture based on this model with six categories of functional blocks to deploy the PLSAs and 3) a description of the implementation of this architecture as an open-source platform to promote the adoption and exploration of this area.
Publisher: Athabasca University Press
Date: 27-08-2014
DOI: 10.19173/IRRODL.V15I4.1878
Abstract: The rapid advances in information and communication technologies, coupled with increased access to information and the formation of global communities, have resulted in interest among researchers and academics to revise educational practice to move beyond traditional ‘literacy’ skills towards an enhanced set of “multiliteracies” or “new media literacies”. Measuring the literacy of a population, in the light of its linkage to in idual and community wealth and wellbeing, is essential to determining the impact of compulsory education. The opportunity now is to develop tools to assess in idual and societal attainment of these new literacies. Drawing on the work of Jenkins and colleagues (2006) and notions of a participatory culture, this paper proposes a conceptual framework for how learning analytics can assist in measuring in idual achievement of multiliteracies and how this evaluative process can be scaled to provide an institutional perspective of the educational progress in fostering these fundamental skills.
Location: Australia
Start Date: 08-2022
End Date: 07-2025
Amount: $389,011.00
Funder: Australian Research Council
View Funded Activity