20 research outputs found
The Impact of Artificial Intelligence on Societies: Understanding Attitude Formation Towards AI
No full textThis is an Author Accepted Manuscript version of the following chapter: Schepman, A. & Rodway, P., The measurement of attitudes towards Artificial Intelligence: An overview and recommendations, published in The Impact of AI on societies: Understanding attitude formation towards AI, edited by Montag, C. & Ali, R. (Eds.) 2025, Springer, reproduced with permission of Springer. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-031-70355-3_2The growth in use of Artificial Intelligence is having a major impact on society, with further impacts anticipated in the coming years and decades. There are individual differences in attitudes towards Artificial Intelligence and it is important for scientists and others to be able to measure these. Individual differences in attitudes towards Artificial Intelligence may be associated with other major psychological or circumstantial factors, and understanding these associations is beneficial. In addition, it is important to be able to track attitudes towards Artificial Intelligence over time. For this purpose, scientists have developed psychometric measurement tools to measure attitudes towards Artificial Intelligence. This Chapter provides an overview and evaluation of these tools, with a focus on tools that measure general attitudes towards Artificial Intelligence, and that are quantitative measurements, which can be analysed statistically. Semantic, methodological, and psychometric factors that the user should consider when choosing a suitable tool are discussed. The choice of measurement tool may depend on many researcher-driven considerations, including time, cost, and practical factors, but the quality and validity of the measurement tool should be a major factor in this choice. A scale’s ability to capture important dimensions in the data should also be a key consideration. We recommend that observed ambivalence about AI is best captured with a bi-dimensional AI attitudes scale.Unfunde
Editorial: Networks and knowledge brokering: advancing foundations, inviting complexity
No full textThis article was originally published in Frontiers in Education by Frontiers Media. The version of record is available at: https://doi.org/10.3389/feduc.2025.1555200.
© 2025 MacGregor, Rodway and Farley-Ripple. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (http://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Framing the Research Topic
As educational ecosystems become increasingly complex and diverse, understanding how knowledge brokerage and relational networks interact can offer pathways for strengthening connections among research, policy, and practice. Knowledge brokers have garnered attention for their capacity to navigate evidence and adapt it for various audiences, while relational networks—spanning professional communities, partnerships, and organizational structures—provide channels through which knowledge flows and evolves. Yet, much of the current literature examines these phenomena independently, and we lack integrated perspectives that clarify how they co-influence policy decision-making, on-the-ground educational change, and system-wide learning.
This Research Topic aims to bridge this gap by examining how knowledge brokers operate within relational networks to cultivate evidence-informed policy and practice in education. Its dual objectives are to advance theoretical and empirical understandings of these intertwined processes and to translate these insights into concrete, actionable guidance for policymakers, educational leaders and practitioners, and researchers.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest
Side preferences in human dyads when walking: the influence of country, threat, handedness, and sex
No full text© 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.In several species, lateral position preferences have been observed in pair mates, mother–infant dyads, and during agonistic interactions. This research examined side preferences in human dyads in an observational study and survey. We observed 1236 male–female pairs walking in the UK and found a bias for males to walk on the right side of the pair, which did not depend on hand-holding, or walking during daylight or darkness. The survey measured side preferences in 798 participants (398 left-handed, 411 right-handed), from the UK (402) and USA (396). Participants chose a side to walk when walking with their partner, or alone, in various threatening/non-threatening scenes. Threat did not influence preference in walking couples, but males, when passing a threatening stranger, preferred the best combat side for their handedness. Country and handedness also influenced preferences. Left-handers preferred the left side and right-handers preferred the right side, and USA participants exhibited a more rightward preference than UK participants. The pattern of preference for each country was equivalent, showing independent influences of handedness and cultural learning. Overall, the results suggest that males and females prefer the side that allows their dominant hand to be on the outside of the dyad.The authors gratefully acknowledge the funding for Study 2, which was provided by an internal University of Chester grant with the grant code QR737
Abstract of Proceedings, October, 1903
No full textThe final evening meeting of the 1903 session was held on 11th inst., Mr. Bernard Shaw presiding. Owing to the inclement weather the attendance was limited. Among those present were:— Bishop Mercer, Messrs. K. M. Johnston, L. Rodway, C. B. Target, and A. O. Green.The secretary referred to the work that Mr. Johnston had done during his residence in Tasmania. The secretary read extracts from Professor Judd, the late Sir Robert Hamilton, and the Rev.Julian Tenison Woods, in which the three named spoke in the highest praise of Mr. Johnston's work on the geology of Tasmania.In the absence of the author (Prof. E. G, Hogg, M.A.) Mr. R. M. Johnston read the paper entitled "The glacial beds at Port Cygnet." It was decided that discussion on this paper should be taken at a future meeting. Mr. R. M. Johnston submitted some interesting notes on specimens of fossil flora and a fossil fish, discovered at Tinder Box Bay, and also some remarks on some fossil shells (Spirifer triangularis). Mr. L. Rodway read two very carefully prepared papers, dealing with some fungi found occurring in Tasmania
Initial validation of the general attitudes towards Artificial Intelligence Scale
No full textAuthor Accepted Manuscript with Appendix A (Sources of News Stories) and Appendix B (General Attitudes Towards Artificial Intelligence Scale, with instructions and scoring). For data files, please follow the DOI https://doi.org/10.1016/j.chbr.2020.100014 to the publisher's site. This article is available Open Access via the Publisher's site: https://www.sciencedirect.com/science/article/pii/S2451958820300142A new General Attitudes towards Artificial Intelligence Scale (GAAIS) was developed. The scale underwent initial statistical validation via Exploratory Factor Analysis, which identified positive and negative subscales. Both subscales captured emotions in line with their valence. In addition, the positive subscale reflected societal and personal utility, whereas the negative subscale reflected concerns. The scale showed good psychometric indices and convergent and discriminant validity against existing measures. To cross-validate general attitudes with attitudes towards specific instances of AI applications, summaries of tasks accomplished by specific applications of Artificial Intelligence were sourced from newspaper articles. These were rated for comfortableness and perceived capability. Comfortableness with specific applications was a strong predictor of general attitudes as measured by the GAAIS, but perceived capability was a weaker predictor. Participants viewed AI applications involving big data (e.g. astronomy, law, pharmacology) positively, but viewed applications for tasks involving human judgement, (e.g. medical treatment, psychological counselling) negatively. Applications with a strong ethical dimension led to stronger discomfort than their rated capabilities would predict. The survey data suggested that people held mixed views of AI. The initially validated two-factor GAAIS to measure General Attitudes towards Artificial Intelligence is included in the Appendix
Abstract of Proceedings, October, 1903
No full textThe final evening meeting of the 1903
session was held on 11th inst., Mr.
Bernard Shaw presiding. Owing to the
inclement weather the attendance was
limited. Among those present were:—
Bishop Mercer, Messrs. K. M. Johnston,
L. Rodway, C. B. Target, and A. O.
Green.The secretary referred to the work that
Mr. Johnston had done during his residence
in Tasmania. The secretary read
extracts from Professor Judd, the late
Sir Robert Hamilton, and the Rev.
Julian Tenison Woods, in which the
three named spoke in the highest praise
of Mr. Johnston's work on the geology of
Tasmania.In the absence of the author (Prof. E.
G, Hogg, M.A.) Mr. R. M. Johnston read the paper entitled "The glacial beds at
Port Cygnet." It was decided that discussion
on this paper should be taken at
a future meeting. Mr. R. M. Johnston submitted some interesting
notes on specimens of fossil
flora and a fossil fish, discovered at Tinder
Box Bay, and also some remarks on
some fossil shells (Spirifer triangularis). Mr. L. Rodway read two very carefully
prepared papers, dealing with some fungi
found occurring in Tasmania
The Sandy Lane villa: its wider context
No full textThis is the author accepted manuscript. The final version is available from Oxbow via the link in this recordNote that the title of the author accepted manuscript is slightly different from the final published titleCotswold Archaeology Monograph series volume 1
Validation of the Short General Attitudes Towards Artificial Intelligence Scale: The Short GAAIS-10
No full text© 2026 The Author(s). Published with license by Taylor & Francis Group, LLC.With Artificial Intelligence becoming ever more widespread, it is important to have instruments that measure people’s attitudes toward Artificial Intelligence efficiently. Providing such a tool was the aim of the current report. Its authors report the validation of a shortened and further purified version of General Attitudes toward Artificial Intelligence Scale (GAAIS) consisting of ten items (Short GAAIS-10) based on empirical survey data from UK-based participants, collected online (total N = 1406). The multi-phase study design was based on Factor Analysis, Item Response Theory, correlation, and multivariate multiple regression. Phase 1 was a rigorous selection phase based on three independent prior samples of approximately 300 participants each (collected in 2021 and 2022). Confirmatory Factor Analysis (CFA) and Polytomous Rasch Analysis (PTA) alongside semantic judgements were used to select 10 items. In phase 2, a new representative UK sample (N = 500) was drawn in 2024 to further validate the Short GAAIS-10. CFA and PTA of the new data revealed good psychometric properties of the Short GAAIS-10, which is bidimensional with two subscales (Positive, Negative). The Short GAAIS-10 showed predictive validity against the Technology Readiness Index based on correlation analysis. Rated comfortableness with seven types of AI applications was positively predicted by the Short GAAIS-10 subscales based on multivariate multiple regression. The Short GAAIS-10 is a valid and streamlined instrument with which to measure General Attitudes toward Artificial Intelligence. The ambivalent nature of public AI attitudes is discussed as an important observation for a general AI attitude scale to capture. The contribution of this research is the creation of a short version of a valid and efficient psychometric instrument with which to measure general attitudes toward Artificial Intelligence.This work was supported by the University of Chester under [Grant QR738]
The early medieval territory associated with Cannington
No full textThis is the author accepted manuscript. The final version is available from Oxbow via the link in this recordCotswold Archaeology Monograph series volume 1
The modified fighting hypothesis of handedness: Evidence from sharp force injuries and further considerations
No full text© 2026 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.The modified fighting hypothesis (MFH) proposes that most humans are right-handed because it conveyed an advantage during intraspecific fights with sharp weapons, due to the leftward location of the heart and aorta. An examination of the literature on sharp force injury showed that the thoracic region is penetrated more than any other region, and the left thorax is penetrated approximately 2.4 times more often than the right thorax. Handedness influenced the side of the thorax targeted, with most right-handers penetrating the left thorax in front of their right hand. As two thirds of the heart is in the left thorax, right-handers appear more likely to injure the heart and other vital structures, increasing their lethality when using a sharp weapon. This difference in lethality may have resulted in a survival advantage for right-handers. We discuss the possibility that increased use of sharp weapons in hominins caused evolutionary changes in anatomical traits, reducing sexual dimorphism and increasing population-level right lateralization. Similarities in lateralized fighting in humans and non-human species are considered and related to the MFH
