Predicting student performance in a blended learning environment using learning management system interaction data

Purpose: Student attritions in tertiary educational institutes may play a significant role to achieve core values leading towards strategic mission and financial well-being. Analysis of data generated from student interaction with learning management systems (LMSs) in blended learning (BL) environments may assist with the identification of students at risk of failing, but to what extent this may be possible is unknown. However, existing studies are limited to address the issues at a significant scale. Design/methodology/approach: This study develops a new approach harnessing applications of machine learning (ML) models on a dataset, that is publicly available, relevant to student attrition to identify potential students at risk. The dataset consists of the data generated by the interaction of students with LMS for their BL environment. Findings: Identifying students at risk through an innovative approach will promote timely intervention in the learning process, such as for improving student academic progress. To evaluate the performance of the proposed approach, the accuracy is compared with other representational ML methods. Originality/value: The best ML algorithm random forest with 85% is selected to support educators in implementing various pedagogical practices to improve students’ learning

The economic viability of an in-home monitoring system in the context of an aged care setting

The aged care sector in Australia faces significant challenges. Although many of these issues have been clearly identified, their urgency has been further highlighted during the COVID-19 pandemic. Technology such as in-home monitoring is one way to address some of these challenges. However, the efficacy of technology must be considered together with its implementation and running costs to ensure that there is a return on investment, and it is economically viable as a solution. A pilot programme was run using the HalleyAssist® in-home monitoring system to test the efficacy of this system. This article focuses on an economic analysis to better understand the financial viability of such systems. Using a secondary analysis approach, the findings identified that revenue could be generated by providing carers with additional services such as real-time monitoring of the client, which can foster deeper relationships with the customer, along with savings of healthcare costs to carers, service providers and Government. Savings are related to the earlier intervention of critical events that are identified by the system, as delays in treatment of some critical events can create much more severe and costly health outcomes. Further health costs savings can be made via trend analysis, which can show more nuanced health deterioration that is often missed. The implementation of preventative measures via this identification can reduce the chances of critical events occurring that have much higher costs. Overall, monitoring systems lead to a transition from a reactive to a preventative services offering, delivering more targeted and personalised care

Improving the Theoretical Understanding Toward Patient-Driven Health Care Innovation Through Online Value Cocreation: Systematic Review.

Background: Patient participation in the health care domain has surged dramatically through the availability of digital health platforms and online health communities (OHCs). Such patient-driven service innovation has both potential and challenges for health care organizations. Over the last 5 years, articles have surfaced that focus on value cocreation in health care services and the importance of engaging patients and other actors in service delivery. However, a theoretical understanding of how to use OHCs for this purpose is still underdeveloped within the health care service ecosystem. Objective: This paper aimed to introduce a theoretical discussion for better understanding of the potential of OHCs for health care organizations, in particular, for patient empowerment. Methods: This literature review study involved a comprehensive search using 12 electronic databases (EMBASE, PsycINFO, Web of Science, Scopus, ScienceDirect, Medical Literature Analysis and Retrieval System Online, PubMed, Elton B Stephens Co [academic], Cumulative Index of Nursing and Allied Health Literature, Accelerated Information Sharing for Law Enforcement, Association for Computing Machinery, and Google Scholar) from 2013 to 2019. A total of 1388 studies were identified from the database search. After removing duplicates and applying inclusion criteria, we thematically analyzed 56 articles using the Braun and Clarke thematic analysis approach. Results: We identified a list of 5 salient themes: Communication extension, improved health literacy for patients and health care organizations, communication transparency with patients, informational and social support for patients, and patient empowerment in self-management. The most frequent theme was communication extension, which covers 39% (22/56) of the literature. This theme reported that an extension of communication between patients, caregivers, and physicians and organizations led to new opportunities to create value with minimal time and cost restrictions. Improved health literacy and communication transparency with patients were the second and third most frequent themes, respectively, covering 26% (15/56) and 25% (14/56) of the literature, respectively. The frequency of these themes indicated that the use of OHCs to generate new knowledge from patients' interactions helped health care organizations to customize treatment plans and establish transparent and effective communication between health care organizations and patients. Furthermore, of the 56 studies, 13 (23%) and 10 (17%) studies contended the opportunity of using OHCs in terms of informational and emotional support and empowering patients in their self-management of diseases. Conclusions: This review enables better understanding of the current state of the art of the online value cocreation and its potential for health care organizations. This study found that the opportunities for health care organizations through enhancement of patient participation and their cocreation of value in digital health platforms have been rapidly increasing. The identified gaps and opportunities in this study would identify avenues for future directions in modernized and more effective value-oriented health care informatics research.</p

Knowledge graph model development for knowledge discovery in dementia research using cognitive scripting and next-generation graph-based database: a design science research approach

Recent studies report doubling numbers of deaths due to dementia. With such an escalating mortality rate related to cognitive decline diseases, like dementia, timely information on contributing factors and knowledge discovery from evidence-based repositories is warranted. A large amount of scholarly knowledge extracted from research findings on dementia can be understood only using human intelligence for arriving at quality inferences. Due to the unstructured data presented in such a massive dataset of scientific articles available online, gaining insights from the knowledge hidden in the literature is complex and time-consuming. Hence, there is a need for developing a knowledge management model to create, query and maintain a knowledge repository of key elements and their relationships extracted from scholarly articles in a structured manner. In this paper, an innovative knowledge discovery computing model to process key findings from unstructured data from scholarly articles by using the design science research (DSR) methodology is proposed. The solution caters to a novel composition of the cognitive script of crucial knowledge related to dementia and its subsequent transformation from unstructured into a structured format using graph-based next-generation infrastructures. The computing model contains three phases to assist the research community to have a better understanding of the related knowledge in the existing unstructured research articles: (i) article collection and construction of cognitive script, (ii) generation of Cypher statements (a knowledge graph query language) and (iii) creation of graph-based repository and visualization. The performance of the computing model is demonstrated by visualizing the outcome of various search criteria in the form of nodes and their relationships. Our results also demonstrate the effectiveness of visual query and navigation highlighting its usability