[{"id":1282,"date":"2026-10-30T02:54:29","date_gmt":"2026-10-30T06:54:29","guid":{"rendered":"https:\/\/blogs.clemson.edu\/catlab\/?p=1282"},"modified":"2026-10-30T02:54:30","modified_gmt":"2026-10-30T06:54:30","slug":"published-cognitive-abilities-and-trust-calibration-understanding-individual-differences-in-automation-trust-dynamics","status":"publish","type":"post","link":"https:\/\/blogs.clemson.edu\/catlab\/2026\/10\/30\/published-cognitive-abilities-and-trust-calibration-understanding-individual-differences-in-automation-trust-dynamics\/","title":{"rendered":"[PUBLISHED] Cognitive abilities and trust calibration: Understanding individual differences in automation trust dynamics"},"content":{"rendered":"\n

Link: https:\/\/authors.elsevier.com\/sd\/article\/S0003-6870(26)00190-0<\/a><\/p>\n\n\n\n


Abstract: Individual differences in cognitive abilities may influence how people form and adjust trust in automated systems, yet the mechanisms underlying this relationship remain poorly understood. This study investigated how three foundational cognitive abilities \u2014 working memory (WM), attention control (AC), and fluid intelligence (Gf) \u2014 shape trust dynamics, particularly focusing on trust decline and recovery after automation failures. Participants (N\u202f=\u202f111) completed cognitive tests measuring WM, AC, and Gf before performing a dual-task paradigm where they monitored an automated memory aid exhibiting varying reliability levels (100%-65%-100%) while completing an arithmetic task. Results revealed that WM and Gf positively predicted trust recovery after automation failures, while AC influenced long-term trust calibration, with high-AC individuals showing more nuanced trust adjustments reflecting system reliability history. Trust decline was uniform across ability levels, suggesting that trust loss may occur rapidly after salient failures. The relationship between abilities and trust may have been partially mediated by automation schemas, with WM negatively correlating with all-or-none thinking about automation. These findings suggest different cognitive abilities play distinct roles in trust dynamics: WM supports monitoring automation performance, Gf enables effective schema updating, and AC facilitates appropriate deployment of these resources for trust calibration. This work advances our understanding of trust mechanisms and has implications for designing automation interfaces that accommodate individual cognitive differences.<\/p>\n\n\n\n

Ku, C., McLaughlin, A. C., Pak, R., & Engle, R. (2027). Cognitive abilities and trust calibration: Understanding individual differences in automation trust dynamics.\u00a0Applied Ergonomics<\/em>,\u00a0140<\/em>(104912), 104912. https:\/\/doi.org\/10.1016\/j.apergo.2026.104912<\/p>\n","protected":false},"excerpt":{"rendered":"

Link: https:\/\/authors.elsevier.com\/sd\/article\/S0003-6870(26)00190-0 Abstract: Individual differences in cognitive abilities may influence how people form and adjust trust in automated systems, yet the mechanisms underlying this relationship remain poorly understood. This study investigated how three foundational cognitive abilities \u2014 working memory (WM), attention control (AC), and fluid intelligence (Gf) \u2014 shape trust dynamics, particularly focusing on trust […]<\/p>\n","protected":false},"author":321,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[14093],"tags":[4945],"coauthors":[20933],"class_list":["post-1282","post","type-post","status-publish","format-standard","hentry","category-lab-news","tag-publications"],"fimg_url":false,"_links":{"self":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1282","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/users\/321"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/comments?post=1282"}],"version-history":[{"count":2,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1282\/revisions"}],"predecessor-version":[{"id":1284,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1282\/revisions\/1284"}],"wp:attachment":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/media?parent=1282"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/categories?post=1282"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/tags?post=1282"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/coauthors?post=1282"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":1278,"date":"2026-09-23T12:55:40","date_gmt":"2026-09-23T16:55:40","guid":{"rendered":"https:\/\/blogs.clemson.edu\/catlab\/?p=1278"},"modified":"2026-10-30T02:55:14","modified_gmt":"2026-10-30T06:55:14","slug":"published-a-new-look-at-the-relationship-between-individual-differences-in-cognitive-abilities-and-automation-assisted-performance","status":"publish","type":"post","link":"https:\/\/blogs.clemson.edu\/catlab\/2026\/09\/23\/published-a-new-look-at-the-relationship-between-individual-differences-in-cognitive-abilities-and-automation-assisted-performance\/","title":{"rendered":"[PUBLISHED] A New Look at the Relationship Between Individual Differences in Cognitive Abilities and Automation-Assisted Performance"},"content":{"rendered":"\n

Link: https:\/\/journals.sagepub.com\/doi\/full\/10.1177\/00187208261485051<\/a><\/p>\n\n\n\n

Abstract<\/h2>\n\n\n\n

Objective<\/h3>\n\n\n\n

This study explored whether and which cognitive abilities are supported by various levels of automation.<\/p>\n\n\n\n

Background<\/h3>\n\n\n\n

Parasuraman\u2019s (2000) model of automation provided guidance for designing automation to augment cognitive tasks. Subsequent mixed empirical findings and evolving understanding of attention control in complex tasks suggested an evaluation of how automation supports cognition within a task was needed.<\/p>\n\n\n\n

Method<\/h3>\n\n\n\n

Participants completed cognitive ability tests then a targeting task either manually or with information automation or decision automation.<\/p>\n\n\n\n

Results<\/h3>\n\n\n\n

Decision automation supported working memory only when reliable, while attention control predicted performance regardless of automation level.<\/p>\n\n\n\n

Conclusion<\/h3>\n\n\n\n

Results suggest automation can support specific processes like working memory, while attention control demands may persist across automation levels. However, because the task involved a relatively constrained form of automation, future research should examine whether these effects hold with more flexible, adaptive systems.<\/p>\n\n\n\n

Application<\/h3>\n\n\n\n

Automation should target specific cognitive functions while recognizing that attention control demands may persist. Future research might investigate how other automation designs can better support this foundational ability.<\/p>\n\n\n\n

Textor, C., Pak, R., McLaughlin, A. C., & Engle, R. (2026). A new look at the relationship between individual differences in cognitive abilities and automation-assisted performance.\u00a0Human Factors<\/em>, (00187208261485051), 187208261485051. https:\/\/doi.org\/10.1177\/00187208261485051<\/p>\n","protected":false},"excerpt":{"rendered":"

Link: https:\/\/journals.sagepub.com\/doi\/full\/10.1177\/00187208261485051 Abstract Objective This study explored whether and which cognitive abilities are supported by various levels of automation. Background Parasuraman\u2019s (2000) model of automation provided guidance for designing automation to augment cognitive tasks. Subsequent mixed empirical findings and evolving understanding of attention control in complex tasks suggested an evaluation of how automation supports cognition […]<\/p>\n","protected":false},"author":321,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[14093],"tags":[4945],"coauthors":[20933],"class_list":["post-1278","post","type-post","status-publish","format-standard","hentry","category-lab-news","tag-publications"],"fimg_url":false,"_links":{"self":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1278","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/users\/321"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/comments?post=1278"}],"version-history":[{"count":2,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1278\/revisions"}],"predecessor-version":[{"id":1285,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1278\/revisions\/1285"}],"wp:attachment":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/media?parent=1278"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/categories?post=1278"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/tags?post=1278"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/coauthors?post=1278"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":1272,"date":"2026-06-09T18:03:40","date_gmt":"2026-06-09T22:03:40","guid":{"rendered":"https:\/\/blogs.clemson.edu\/catlab\/?p=1272"},"modified":"2026-06-09T18:03:40","modified_gmt":"2026-06-09T22:03:40","slug":"published-genai-as-complete-cognitive-automation-for-untrained-users-at-population-scale-implications-for-human-factors-and-ergonomics","status":"publish","type":"post","link":"https:\/\/blogs.clemson.edu\/catlab\/2026\/06\/09\/published-genai-as-complete-cognitive-automation-for-untrained-users-at-population-scale-implications-for-human-factors-and-ergonomics\/","title":{"rendered":"[PUBLISHED] GenAI as complete cognitive automation for untrained users at population scale: implications for human factors and ergonomics"},"content":{"rendered":"\n

Abstract<\/h2>\n\n\n\n

Generative AI (GenAI) systems provide complete cognitive task outputs to untrained users across unrestricted domains at population scale, creating an unprecedented form of automation. We use a foundational four-stage model of automation (information acquisition, information analysis, decision selection, and action specification) to characterise the shift: GenAI automates all four stages simultaneously. Yet the classical automation effects (such as the \u2018lumberjack effect\u2019) were established exclusively in trained operators working within bounded domains. Whether these effects persist, intensify, or transform when GenAI violates all of these scope conditions at once remains an open empirical question. Nearly a billion people now use this technology without the empirical foundation needed to predict its consequences for human performance. This commentary maps how GenAI\u2019s deployment configuration exceeds the empirical boundaries of automation theory and identifies the critical research questions needed to guide investigation of human performance and safety in this understudied area of automation design.<\/p>\n\n\n\n

Download link: https:\/\/www.tandfonline.com\/eprint\/ZK4XGUWSY4G3RI88VFGI\/full?target=10.1080\/00140139.2026.2686284<\/a><\/p>\n\n\n\n

Pak, R., Rovira, E., & McLaughlin, A. (2026). GenAI as complete cognitive automation for untrained users at population scale: implications for human factors and ergonomics.\u00a0Ergonomics<\/em>, 1\u201314. https:\/\/doi.org\/10.1080\/00140139.2026.2686284<\/p>\n","protected":false},"excerpt":{"rendered":"

Abstract Generative AI (GenAI) systems provide complete cognitive task outputs to untrained users across unrestricted domains at population scale, creating an unprecedented form of automation. We use a foundational four-stage model of automation (information acquisition, information analysis, decision selection, and action specification) to characterise the shift: GenAI automates all four stages simultaneously. Yet the classical […]<\/p>\n","protected":false},"author":321,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[14093],"tags":[],"coauthors":[20933],"class_list":["post-1272","post","type-post","status-publish","format-standard","hentry","category-lab-news"],"fimg_url":false,"_links":{"self":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1272","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/users\/321"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/comments?post=1272"}],"version-history":[{"count":0,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1272\/revisions"}],"wp:attachment":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/media?parent=1272"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/categories?post=1272"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/tags?post=1272"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/coauthors?post=1272"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":1270,"date":"2024-12-04T10:32:28","date_gmt":"2024-12-04T15:32:28","guid":{"rendered":"https:\/\/blogs.clemson.edu\/catlab\/?p=1270"},"modified":"2024-12-04T11:07:09","modified_gmt":"2024-12-04T16:07:09","slug":"published-the-role-of-automation-etiquette-and-task-criticality-on-performance-workload-automation-reliance-and-user-confidence","status":"publish","type":"post","link":"https:\/\/blogs.clemson.edu\/catlab\/2024\/12\/04\/published-the-role-of-automation-etiquette-and-task-criticality-on-performance-workload-automation-reliance-and-user-confidence\/","title":{"rendered":"[PUBLISHED] The role of automation etiquette and task-criticality on performance, workload, automation reliance, and user confidence"},"content":{"rendered":"\n

Abstract<\/h2>\n\n\n\n

Previous research suggests good automation etiquette can yield positive effects on user performance, trust, automation reliance, and user confidence \u2013 especially in personified or anthropomorphized technologies. The current study examined the impact of automation etiquette and task-criticality in non-personified technology. The study used a computer-based automation task to examine good and bad automation etiquette models and different domain-based task-criticality levels (between-subjects) that contained various stages of automation (stage 2 and stage 3) and automation reliability levels (60% and 80%) (within-subjects). The study found that bad automation etiquette can increase automation bias and automation reliance which improved performance in the most capable automation condition (stage 3; 80% reliable) but also heightened user subjective workload and decreased user self-confidence. The study also demonstrated task-criticality can be successfully manipulated through domain and instructions. Overall, automation etiquette influenced performance and user confidence more in highly capable automation (stage 3) and in a low-criticality task domain.<\/p>\n\n\n\n

Link to paper<\/a><\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

Abstract Previous research suggests good automation etiquette can yield positive effects on user performance, trust, automation reliance, and user confidence \u2013 especially in personified or anthropomorphized technologies. The current study examined the impact of automation etiquette and task-criticality in non-personified technology. The study used a computer-based automation task to examine good and bad automation etiquette […]<\/p>\n","protected":false},"author":321,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[14093],"tags":[],"coauthors":[20933],"class_list":["post-1270","post","type-post","status-publish","format-standard","hentry","category-lab-news"],"fimg_url":false,"_links":{"self":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1270","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/users\/321"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/comments?post=1270"}],"version-history":[{"count":0,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1270\/revisions"}],"wp:attachment":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/media?parent=1270"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/categories?post=1270"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/tags?post=1270"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/coauthors?post=1270"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":1267,"date":"2024-11-29T06:22:00","date_gmt":"2024-11-29T11:22:00","guid":{"rendered":"https:\/\/blogs.clemson.edu\/catlab\/?p=1267"},"modified":"2024-11-29T05:24:21","modified_gmt":"2024-11-29T10:24:21","slug":"published-polite-ai-mitigates-user-susceptibility-to-ai-hallucinations","status":"publish","type":"post","link":"https:\/\/blogs.clemson.edu\/catlab\/2024\/11\/29\/published-polite-ai-mitigates-user-susceptibility-to-ai-hallucinations\/","title":{"rendered":"[PUBLISHED] Polite AI mitigates user susceptibility to AI hallucinations"},"content":{"rendered":"\n

Pak, R., Rovira, E., & McLaughlin, A. C. (in press). Polite AI mitigates user susceptibility to AI hallucinations. Ergonomics<\/em>. https:\/\/doi.org\/10.1080\/00140139.2024.2434604<\/a>
<\/p>\n\n\n\n

Abstract<\/h2>\n\n\n\n

With their increased capability, AI-based chatbots have become increasingly popular tools to help users answer complex queries. However, these chatbots may hallucinate, or generate incorrect but very plausible-sounding information, more frequently than previously thought. Thus, it is crucial to examine strategies to mitigate human susceptibility to hallucinated output. In a between-subjects experiment, participants completed a difficult quiz with assistance from either a polite or neutral-toned AI chatbot, which occasionally provided hallucinated (incorrect) information. Signal detection analysis revealed that participants interacting with polite-AI showed modestly higher sensitivity in detecting hallucinations and a more conservative response bias compared to those interacting with neutral-toned AI. While the observed effect sizes were modest, even small improvements in users\u2019 ability to detect AI hallucinations can have significant consequences, particularly in high-stakes domains or when aggregated across millions of AI interactions.<\/p>\n\n\n\n

Practitioner Summary<\/h2>\n\n\n\n

This study examined how AI chatbot etiquette affects users\u2019 susceptibility to AI hallucinations. Through a controlled experiment, results showed polite-AI led to modestly higher sensitivity in detecting hallucinations and a more conservative response bias. This suggests a potential design strategy that may enhance users\u2019 critical evaluation of AI-generated content.<\/p>\n","protected":false},"excerpt":{"rendered":"

Pak, R., Rovira, E., & McLaughlin, A. C. (in press). Polite AI mitigates user susceptibility to AI hallucinations. Ergonomics. https:\/\/doi.org\/10.1080\/00140139.2024.2434604 Abstract With their increased capability, AI-based chatbots have become increasingly popular tools to help users answer complex queries. However, these chatbots may hallucinate, or generate incorrect but very plausible-sounding information, more frequently than previously thought. […]<\/p>\n","protected":false},"author":321,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[14093],"tags":[4945],"coauthors":[20933],"class_list":["post-1267","post","type-post","status-publish","format-standard","hentry","category-lab-news","tag-publications"],"fimg_url":false,"_links":{"self":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1267","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/users\/321"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/comments?post=1267"}],"version-history":[{"count":0,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1267\/revisions"}],"wp:attachment":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/media?parent=1267"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/categories?post=1267"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/tags?post=1267"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/coauthors?post=1267"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":1266,"date":"2024-11-29T06:19:00","date_gmt":"2024-11-29T11:19:00","guid":{"rendered":"https:\/\/blogs.clemson.edu\/catlab\/?p=1266"},"modified":"2024-11-29T05:25:00","modified_gmt":"2024-11-29T10:25:00","slug":"published-attention-control-measures-improve-the-prediction-of-performance-in-navy-traineespublished","status":"publish","type":"post","link":"https:\/\/blogs.clemson.edu\/catlab\/2024\/11\/29\/published-attention-control-measures-improve-the-prediction-of-performance-in-navy-traineespublished\/","title":{"rendered":"[PUBLISHED] Attention control measures improve the prediction of performance in navy trainees"},"content":{"rendered":"\n

Burgoyne, A. P., Mashburn, C. A., Tsukahara, J. S., Pak, R.<\/strong>, Coyne, J. T., Foroughi, C., Sibley, C., Drollinger, S. M., & Engle, R. W. (in press). Attention control measures improve the prediction of performance in navy trainees. International Journal of Selection and Assessment<\/em>. https:\/\/doi.org\/10.1111\/ijsa.12510<\/a>
<\/p>\n\n\n\n

Abstract<\/h2>\n\n\n\n

Military selection tests leave room for improvement when predicting work-relevant outcomes. We tested whether measures of attention control, working memory capacity, and fluid intelligence improved the prediction of training success above and beyond composite scores used by the U.S. Military. For student air traffic controllers, commonality analyses revealed that attention control explained 9.1% (<\/span>R<\/i>\u2009=\u2009.30) of the unique variance in academic performance, whereas the Armed Forces Qualification Test explained 5.2% (<\/span>r<\/i>\u2009=\u2009.23) of the unique variance. For student naval aviators, incremental validity estimates were small and nonsignificant. For student naval flight officers, commonality analyses revealed that attention control measures explained 11.8% (<\/span>R<\/i>\u2009=\u2009.34) of the unique variance in aviation preflight indoctrination training performance and 4.3% (<\/span>R<\/i>\u2009=\u2009.21) of the unique variance in flight performance. Although these point estimates are based on relatively small samples, they provide preliminary evidence that attention control measures might improve training outcome classification accuracy in real-world samples of military personnel.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Burgoyne, A. P., Mashburn, C. A., Tsukahara, J. S., Pak, R., Coyne, J. T., Foroughi, C., Sibley, C., Drollinger, S. M., & Engle, R. W. (in press). Attention control measures improve the prediction of performance in navy trainees. International Journal of Selection and Assessment. https:\/\/doi.org\/10.1111\/ijsa.12510 Abstract Military selection tests leave room for improvement when predicting […]<\/p>\n","protected":false},"author":321,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[14093],"tags":[4945],"coauthors":[20933],"class_list":["post-1266","post","type-post","status-publish","format-standard","hentry","category-lab-news","tag-publications"],"fimg_url":false,"_links":{"self":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1266","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/users\/321"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/comments?post=1266"}],"version-history":[{"count":0,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/posts\/1266\/revisions"}],"wp:attachment":[{"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/media?parent=1266"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/categories?post=1266"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/tags?post=1266"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/blogs.clemson.edu\/catlab\/wp-json\/wp\/v2\/coauthors?post=1266"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":1263,"date":"2024-08-27T07:43:20","date_gmt":"2024-08-27T11:43:20","guid":{"rendered":"https:\/\/blogs.clemson.edu\/catlab\/?p=1263"},"modified":"2024-08-27T07:43:20","modified_gmt":"2024-08-27T11:43:20","slug":"psychology-professor-receives-funding-to-examine-the-role-of-cognition-in-human-autonomy-collaboration","status":"publish","type":"post","link":"https:\/\/blogs.clemson.edu\/catlab\/2024\/08\/27\/psychology-professor-receives-funding-to-examine-the-role-of-cognition-in-human-autonomy-collaboration\/","title":{"rendered":"Psychology professor receives funding to examine the role of cognition in human-autonomy collaboration"},"content":{"rendered":"\n

Richard Pak, psychology professor and director of the Human Factors Institute at Clemson University, has received more than $560,000 from the National Science Foundation (NSF) to examine how cognitive abilities, including attention and memory, influence users\u2019 performance with automated systems.<\/p><\/blockquote>\n\n\n\n

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Psychology professor receives funding to examine the role of cognition in human-autonomy collaboration<\/a><\/blockquote>