ORCID Profile
0000-0001-7309-4915
Current Organisations
The University of Newcastle
,
University of Texas at San Antonio
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Publisher: Elsevier BV
Date: 12-2023
Publisher: Springer Science and Business Media LLC
Date: 14-01-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Center for Open Science
Date: 31-08-2021
Abstract: Numerals are part of our everyday lives and are regularly viewed in less-than ideal conditions. Mistaking one numeral for another is almost an inevitability, and the cost of these confusions could be insignificant or hugely expensive! Numeral confusions can be explained by distances between our mental representations — how we internally represent the external world — resulting from their perceived similarities yet, how expertise interacts with the mental space of numerals is largely unexplored. We used an identification paradigm to investigate the mental representations of familiar and unfamiliar numerals (4 sets: Arabic, Chinese, Thai, and non-symbolic dots) in a first-language English and a first-language Chinese speaking cohort. Using Luce's choice model, we removed the undesired effect of response bias and conducted multidimensional scaling analyses. Results showed that expertise with numerals alters distances in the mental space, that unfamiliar numerals are represented identically across cultures, that non-symbolic numerals (dots) may be represented both perceptually and numerically in the mental space, and that Arabic, Thai and Chinese numerals are represented by their perceptual similarities. The findings and methods of this study provide a principled foundation for future investigations into how expertise shapes people's mental representations.
Publisher: Center for Open Science
Date: 30-08-2022
Abstract: Collaboration in shared environments requires human agents to coordinate their behaviour according to the machines’ actions. In this study, we compared the performance and behaviour of Human-Machine (HM) and Human-Human (HH) teams. While HH teaming behaviour is sensitive to Collaborative contexts, little is known about HM teaming behaviour. Furthermore, teaming behaviour may impact the team’s Joint Capacity – the team’s ability to handle teamwork processes and task demands. To assess teaming behaviour at every moment of a trial we used three distinct spatiotemporal measures (Momentary Distance, Highly Correlated Segments, and Running Correlation). To assess the team’s joint performance, we adopted the Capacity Coefficient (Townsend & Nozawa,1995). For both HH and HM teams, behavioural measures predicted Joint Capacity. HH teams demonstrated greater performance and less synchronous behaviour than HM teams. The reduced synchrony of HH teams likely improved their performance as they could complement each other’s behaviour ratherthan duplicate inefficiencies
Publisher: Center for Open Science
Date: 09-2022
Abstract: In the modern world, there are important tasks that have become too complex for a single unaided in idual to manage. Some safety-critical tasks are conducted by teams to improve task performance and minimize risk of error. These teams have traditionally consisted of human operators, yet nowadays AI and machine systems are incorporated into team environments to improve performance and capacity. We used a computerized task, modeled after a classic arcade game, to investigate the performance of human-machine and human-human teams. We manipulated the group conditions between team members sometimes they were incentivised to collaborate, sometimes compete, and sometimes to work separately. We evaluated players’ performance in the main task (game play) and also measured the cognitive workload they experienced. We compared workload and game performance between different team types (human-human vs. human-machine) and different group conditions (competitive, collaborate, independent). Adapting workload capacity analysis to human-machine teams, we found performance under both team types and all group conditions suffered a performance efficiency cost. However, we observed a reduced cost in collaborative over competitive teams within human-human pairings but this effect was diminished when playing with a machine partner. The implications of workload capacity analysis as a powerful tool for human-machine team performance measurement are discussed.
Publisher: Center for Open Science
Date: 09-08-2022
Abstract: Discrete choice (DCE) and rating scale experiments (RSE) are commonly applied procedures for eliciting preference judgments in a plethora of applied settings such as consumer choices, health care, and transport economics. An almost universal assumption is that actual "ground truth" preferences do not depend on which elicitation procedure is used. It is usually not possible to test this assumption, because typical studies feature response options for which there is no objectively correct response. To make progress on testing this assumption, we conducted a perceptual discrimination experiment where response options varied on a single attribute -- stimulus saturation level -- with a known objectively correct response. We had the same participants complete both a choice task (CT) and rating scale (RS) version of the experiment, allowing a direct examination of the assumption of a common representation. Our CT featured many characteristics that define a DCE, however, in order to have a known objectively correct response, it also differed in a few important ways. To test the assumption of a common representation, we developed a cognitive model with a response mechanism for both CT and RS. This enabled us to compare a model version that featured one shared latent stimulus representation across CT and RS versus a version which featured separate representations. Our results support the assumption that a single internal state supports both CT and RS responses, and also suggest that the CT method might provide more sensitive measurement of internal states than the RS method.
Publisher: Springer Science and Business Media LLC
Date: 30-11-2020
DOI: 10.1186/S41235-020-00259-W
Abstract: In a Dutch auction, an item is offered for sale at a set maximum price. The price is then gradually lowered over a fixed interval of time until a bid is made, securing the item for the bidder at the current price. Bidders must trade-off between certainty and price: bid early to secure the item and you pay a premium bid later at a lower price but risk losing to another bidder. These properties of Dutch auctions provide new opportunities to study competitive decision-making in a group setting. We developed a novel computerised Dutch auction platform and conducted a set of experiments manipulating volatility (fixed vs varied number of items for sale) and price reduction interval rate (step-rate). Triplets of participants ( $$N=66$$ N = 66 ) competed with hypothetical funds against each other. We report null effects of step-rate and volatility on bidding behaviour. We developed a novel adaptation of prospect theory to account for group bidding behaviour by balancing certainty and subjective expected utility. We show the model is sensitive to variation in auction starting price and can predict the associated changes in group bid prices that were observed in our data.
Publisher: Center for Open Science
Date: 22-08-2019
Abstract: People express quantities using a remarkably small set of units – digits. Confusing digits could be costly, and not all confusions are equal confusing a price tag of 2 dollars with 9 dollars is naturally more costly than confusing 2 with 3. Confusion patterns are intimately related to the distances between mental representations, which are hypothetical internal symbols said to stand for, or represent, ‘real’ external stimuli. The distance between the mental representations of two digits could be determined by their numerical distance. Alternatively, it could be driven by visual similarity. In an English speaking cohort, we investigated the mental representations of familiar and unfamiliar numbers (4 sets: Arabic, Chinese, Thai, and non-symbolic dots) through a set of identification experiments, using multi-dimensional scaling and cluster analysis. We controlled for undesired effects of response bias using Luce’s choice model. Our findings show Arabic, Chinese and Thai numerals were represented in the mental space by perceptual similarities. We also find non-symbolic dots were represented by perceptual and numerical similarities. This work is a novel contribution to the literature and lays the foundation for further investigations into the mental representation of numerals across cultures.
Location: United States of America
Location: Australia
No related grants have been discovered for Murray Bennett.