Jane E. Klobas, Tanya J. McGill, Sedigheh Moghavvemi and Tanuosha Paramanathan
The purpose of this paper is to present brief YouTube life stories to learn about how extensive users experience YouTube use and manage (or fail to manage) their use. It also…
Abstract
Purpose
The purpose of this paper is to present brief YouTube life stories to learn about how extensive users experience YouTube use and manage (or fail to manage) their use. It also explores the consequences of different types of extensive use.
Design/methodology/approach
In this paper, a biographical approach was used. Nine students who used YouTube for two or more hours every day were guided to tell life stories of their introduction to YouTube, subsequent use and critical events associated with YouTube use. Thematic analysis distinguished between non-problematic, compulsive and addicted users. Three single case life stories illustrate the experiences of users in each category.
Findings
These extensive YouTube users tell similar stories of informal learning from early interaction with the platform. For some, extensive YouTube use became problematic; for others, it remained functional. Similar to other social platforms, users unable to regulate use became compulsive users and some users can become addicted. While the symptoms of YouTube addiction are similar to other online addictions, compulsive YouTube use is driven more by algorithm-generated content chaining than overt social interaction.
Originality/value
The paper introduces life stories as a way to present case studies of social media use. The distinction between extensive, but functional, and problematic YouTube use illustrates how extensive social media use is not necessarily dysfunctional. User education for self-regulation of YouTube use is recommended.
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Information technology users often fail to adopt necessary security and privacy measures, leading to increased risk of cybercrimes. There has been limited research on how…
Abstract
Purpose
Information technology users often fail to adopt necessary security and privacy measures, leading to increased risk of cybercrimes. There has been limited research on how demographic differences influence information security behaviour and understanding this could be important in identifying users who may be more likely to have poor information security behaviour. This study aims to investigate whether there are any gender differences in security and privacy behaviours and perceptions, to identify potential differences that may have implications for protecting users’ privacy and securing their devices, software and data.
Design/methodology/approach
This paper addresses this research gap by investigating security behaviours and perceptions in the following two studies: one focussing on information security and one on information privacy. Data was collected in both studies using anonymous online surveys.
Findings
This study finds significant differences between men and women in over 40% of the security and privacy behaviours considered, suggesting that overall levels of both are significantly lower for women than for men, with behaviours that require more technical skill being adopted less by female users. Furthermore, individual perceptions exhibited some gender differences.
Originality/value
This research suggests that potential gender differences in some security and privacy behaviours and perceptions should be taken into account when designing information security education, training and awareness initiatives for both organisations and the broader community. This study also provides a strong foundation to explore information security individual differences more deeply.
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Tanya Fitzgerald and Sally Knipe
Teacher colleges played a significant role in the preparation of teachers for over 100 years in New Zealand. Teacher training colleges opened in the 1880s and served as the main…
Abstract
Teacher colleges played a significant role in the preparation of teachers for over 100 years in New Zealand. Teacher training colleges opened in the 1880s and served as the main institutions for teacher preparation. Toward the end of the twentieth century, the plight of teachers’ colleges once again fell victim to the ‘decline and demand cycle’ for teachers. Fueled by discussions regarding the extent teacher training should be “practically based in the classroom”, new government directions and policy priorities for the preparation of the teaching workforce were implemented. All teacher colleges experienced either staged amalgamations or ultimate closure. In the late 1970s and 1980s, the preparation of teachers entered a new phase as the responsibility shifted to the university sector, which included the training of kindergarten teachers. While the policy rhetoric imagined this to be an amalgamation, the reality was a process fraught with a number of anxieties, not the least of which were the intellectual shifts.
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Tanya Chichekian and Bruce M. Shore
This chapter overviews the articulation of inquiry in the three International Baccalaureate (IB) levels, Primary Years (ages 3–12), Middle Years (11–16), and the Diploma Program…
Abstract
This chapter overviews the articulation of inquiry in the three International Baccalaureate (IB) levels, Primary Years (ages 3–12), Middle Years (11–16), and the Diploma Program (16–18) that is widely accepted by universities for matriculation. It reviews inquiry-based instruction in the publicly available IB research literature. The IB advocates inquiry as its pedagogical approach. We identified empirical classroom research involving IB teachers or students from four databases; 35 reports matched inclusion criteria and 31 of these had appeared in gifted-education journals. The IB’s inquiry philosophy, interdisciplinary emphasis, and specific elements in the Diploma Program such as the Theory of Knowledge course, a program entitled Creativity, Action, and Service, and the Extended Essay, comprise qualities that should inform higher education. There has been disproportionate attention to the planning part of inquiry (e.g., generating worthy questions and deciding how to answer them) versus enactment or reflection; this leaves room for other research input about enacting inquiry in university instruction that creates a cycle of creative engagement. Successful IB experiences, through some of the IB pedagogy and content, raised learners’ expectations about their higher education learning experiences. However, as one moves from the Primary Years through to the Diploma Program, students report increasing “teaching to the test” and content-coverage that constrain inquiry opportunities students value. The importance of providing detailed, supportive, step-by-step introductions to inquiry, and attending to the social and emotional correlates of the substantive learning, were highlighted.
Thalia Anthony, Juanita Sherwood, Harry Blagg and Kieran Tranter
Tao Chen, Tanya Froehlich, Tingyu Li and Long Lu
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is difficult to diagnose accurately due to its heterogeneous clinical manifestations. Comprehensive…
Abstract
Purpose
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is difficult to diagnose accurately due to its heterogeneous clinical manifestations. Comprehensive models combining different big data approaches (e.g. neuroimaging, genetics, eye tracking, etc.) may offer the opportunity to characterize ASD from multiple distinct perspectives. This paper aims to provide an overview of a novel diagnostic approach for ASD classification and stratification based on these big data approaches.
Design/methodology/approach
Multiple types of data were collected and recorded for three consecutive years, including clinical assessment, neuroimaging, gene mutation and expression and response signal data. The authors propose to establish a classification model for predicting ASD clinical diagnostic status by integrating the various data types. Furthermore, the authors suggest a data-driven approach to stratify ASD into subtypes based on genetic and genomic data.
Findings
By utilizing complementary information from different types of ASD patient data, the proposed integration model has the potential to achieve better prediction performance than models focusing on only one data type. The use of unsupervised clustering for the gene-based data-driven stratification will enable identification of more homogeneous subtypes. The authors anticipate that such stratification will facilitate a more consistent and personalized ASD diagnostic tool.
Originality/value
This study aims to utilize a more comprehensive investigation of ASD-related data types than prior investigations, including proposing longitudinal data collection and a storage scheme covering diverse populations. Furthermore, this study offers two novel diagnostic models that focus on case-control status prediction and ASD subtype stratification, which have been under-explored in the prior literature.