Aim/Purpose: The aim of this project was to explore student perceptions of the value of both the creation of video content and exposure to other students’ work though peer assessment and inclusion of exemplars as unit material. Background: The research was in a first year information technology flipped-learning unit, where the assessment involved students developing video presentations that were peer assessed and exemplars incorporated into the unit as teaching material. Methodology: Data was gathered using a mixed methods approach using an online questionnaire followed by semi-structured interviews with a selection of questionnaire respondents. The interviews were designed to further explore issues identified from the analysis of the questionnaire data. Contribution: Informs on student perceptions of peer review and the integration of student generated content into University teaching. Findings: Most students enjoyed the video assessment (58%) with many preferring it to a written or programming task (55-58%). In the subsequent peer assessment, many liked seeing the work of others (67%) and found the approach engaging (63%) yet some other perceptions were mixed or neutral. Recommendations for Practitioners: University IT students generally enjoyed and perceived peer assessment and found student generated content to be valuable. Recommendation for Researchers: Further investigation of peer review and student generated content in contexts where the student cohort represents a variety of cultures and age categories Impact on Society: Contributes to a body of knowledge regarding peer assessment and student generated educational materials. Future Research: Future work is needed to better understand this domain, in particular the role of learners’ individual differences in order to successfully integrate these approaches into modern learning environments.

Table of Contents for IISIT Volume 15, 2018

Aim/Purpose: Teachers are being asked to integrate mobile technologies into their content creation and distribution tasks. This research aims to provide an understanding of teachers taking on this process and whether the use of technology has influenced their content creation and distribution in the classroom. Background: Many claim that the use of technology for content creation and distribution can only enhance and improve the educational experience. However, for teachers it is not simply the integration of technology that is of prime concern. As teachers are ultimately responsible for the success of technology integration, it is essential to understand teachers’ viewpoints and lived technology experiences. Methodology: The Task-Technology Fit (TTF) model was used to guide interpretive case study research. Six teachers were purposively sampled and interviewed from a private school where a digital strategy is already in place. Data was then analysed using directed content analysis in relation to TTF. Contribution: This paper provides an understanding of teachers’ mobile technology choices in relation to content creation and distribution tasks. Findings: Findings indicate that teachers fit technology into their tasks if they perceive the technology has a high level of benefit to the teaching task. In addition, the age of learners and the subject being taught are major influencers. Recommendations for Practitioners: Provides a more nuanced and in-depth understanding of teachers’ technology choices, which is necessary for the technology augmented educational experience of the future. Recommendations for Researchers: Provides an unbiased and theoretically guided view of mobile technology use with content creation and distribution tasks. Impact on Society: Teachers do not appear to use technology as a de facto standard, but specifically select technology which will save them time, reduce costs, and improve the educational experiences of their learners. Future Research: A mixed-method approach, including several diverse schools as well as learners would enrich the findings. Furthermore, consideration of hardware limitations and lack of software features are needed.

Table of Contents for IISIT Volume 16, 2019

Table of Contents for IISIT Volume 17, 2020

Table of Contents for IISIT Volume 19, 2022

Table of Contents for IISIT Volume 19, 2022

Table of Contents for IISIT Volume 20, 2023

Table of Contents for IISIT Volume 21, 2024

Table of Contents for Volume 15, 2020, of the Interdisciplinary Journal of Information, Knowledge, and Management

Table of Contents for Volume 16, 2021, of the Interdisciplinary Journal of Information, Knowledge, and Management

Table of Contents for Volume 17, 2022, of the Interdisciplinary Journal of Information, Knowledge, and Management

Aim/Purpose: The objective of this research is to investigate the effect of review consistency between textual content and rating on review helpfulness. A measure of review consistency is introduced to determine the degree to which the review sentiment of textual content conforms with the review rating score. A theoretical model grounded in signaling theory is adopted to explore how different variables (review sentiment, review rating, review length, and review rating variance) affect review consistency and the relationship between review consistency and review helpfulness. Background: Online reviews vary in their characteristics and hence their different quality features and degrees of helpfulness. High-quality online reviews offer consumers the ability to make informed purchase decisions and improve trust in e-commerce websites. The helpfulness of online reviews continues to be a focal research issue regardless of the independent or joint effects of different factors. This research posits that the consistency between review content and review rating is an important quality indicator affecting the helpfulness of online reviews. The review consistency of online reviews is another important requirement for maintaining the significance and perceived value of online reviews. Incidentally, this parameter is inadequately discussed in the literature. A possible reason is that review consistency is not a review feature that can be readily monitored on e-commerce websites. Methodology: More than 100,000 product reviews were collected from Amazon.com and preprocessed using natural language processing tools. Then, the quality reviews were identified, and relevant features were extracted for model training. Machine learning and sentiment analysis techniques were implemented, and each review was assigned a consistency score between 0 (not consistent) and 1 (fully consistent). Finally, signaling theory was employed, and the derived data were analyzed to determine the effect of review consistency on review helpfulness, the effect of several factors on review consistency, and their relationship with review helpfulness. Contribution: This research contributes to the literature by introducing a mathematical measure to determine the consistency between the textual content of online reviews and their associated ratings. Furthermore, a theoretical model grounded in signaling theory was developed to investigate the effect on review helpfulness. This work can considerably extend the body of knowledge on the helpfulness of online reviews, with notable implications for research and practice. Findings: Empirical results have shown that review consistency significantly affects the perceived helpfulness of online reviews. The study similarly finds that review rating is an important factor affecting review consistency; it also confirms a moderating effect of review sentiment, review rating, review length, and review rating variance on the relationship between review consistency and review helpfulness. Overall, the findings reveal the following: (1) online reviews with textual content that correctly explains the associated rating tend to be more helpful; (2) reviews with extreme ratings are more likely to be consistent with their textual content; and (3) comparatively, review consistency more strongly affects the helpfulness of reviews with short textual content, positive polarity textual content, and lower rating scores and variance. Recommendations for Practitioners: E-commerce systems should incorporate a review consistency measure to rank consumer reviews and provide customers with quick and accurate access to the most helpful reviews. Impact on Society: Incorporating a score of review consistency for online reviews can help consumers access the best reviews and make better purchase decisions, and e-commerce systems improve their business, ultimately leading to more effective e-commerce. Future Research: Additional research should be conducted to test the impact of review consistency on helpfulness in different datasets, product types, and different moderating variables.

Table of Contents for Volume 18, 2023, of the Interdisciplinary Journal of Information, Knowledge, and Management

Table of Contents for Volume 19, 2024, of the Interdisciplinary Journal of Information, Knowledge, and Management

Table of Contents of the Interdisciplinary Journal of E-Skills and Lifelong Learning

Table of Contents of the Interdisciplinary Journal of E-Skills and Lifelong Learning

Table of Contents of the Interdisciplinary Journal of E-Skills and Lifelong Learning