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What do people in different cultures do when they encounter complex problems? Whereas some cross-cultural research exists about complex problem-solving predictors and performance, the process has rarely been studied. We presented participants from Brazil, Germany, the Philippines, and the United States with two computer-simulated dynamic problems, one where quick action was required - the WinFire simulation - and one where cautious action was required - the Coldstore simulation. Participants were asked to think aloud in their native language while working on these two tasks. These think-aloud protocols were digitally recorded, transcribed, and coded by coders in each country in terms of the steps involved in complex problem solving and dynamic decision making. For the current study, we developed a program to calculate transition frequencies from one problem solving step to another and analyzed only those protocols with more than 15 transitions. For WinFire, these were 256 think-aloud protocols from the four countries with a total of 12,542 statement, for Coldstore, these were 247 participants with a total of 15,237 statements. Based on previous, limited cross-cultural research, we predicted that after identifying a problem, Brazilians would make emotional and self-related statements, Germans would engage primarily in planning, Filipinos would gather additional information, and Americans would primarily state solutions. Results of latent transition analysis partially support these hypotheses, but only in the highly uncertain Coldstore situation and not in the more transparent WinFire situation. Transition frequencies were then also analyzed regarding community clusters using the spinglass algorithm in R, igraph. Results highlight the importance of process analyses in different tasks and show how cultural background guides people's decisions under uncertainty. [ABSTRACT FROM AUTHOR]

What do people in different cultures do when they encounter complex problems? Whereas some cross-cultural research exists about complex problem-solving predictors and performance, the process has rarely been studied. We presented participants from Brazil, Germany, the Philippines, and the United States with two computer-simulated dynamic problems, one where quick action was required – the WinFire simulation – and one where cautious action was required – the Coldstore simulation. Participants were asked to think aloud in their native language while working on these two tasks. These think-aloud protocols were digitally recorded, transcribed, and coded by coders in each country in terms of the steps involved in complex problem solving and dynamic decision making. For the current study, we developed a program to calculate transition frequencies from one problem solving step to another and analyzed only those protocols with more than 15 transitions. For WinFire, these were 256 think-aloud protocols from the four countries with a total of 12,542 statement, for Coldstore, these were 247 participants with a total of 15,237 statements. Based on previous, limited cross-cultural research, we predicted that after identifying a problem, Brazilians would make emotional and self-related statements, Germans would engage primarily in planning, Filipinos would gather additional information, and Americans would primarily state solutions. Results of latent transition analysis partially support these hypotheses, but only in the highly uncertain Coldstore situation and not in the more transparent WinFire situation. Transition frequencies were then also analyzed regarding community clusters using the spinglass algorithm in R, igraph. Results highlight the importance of process analyses in different tasks and show how cultural background guides people’s decisions under uncertainty.

With the advent and integration of technology in business, marketers started investing in numerous media platforms to influence the consumer's sentiments. Artificial intelligence has been proved as one of the innovative tools of digitalization to change consumer's media habits. Owing to the growing trends of e-commerce, the traditional advertising model is insufficient. Therefore, advertisers are taking advantage of artificial intelligence technology to meet current requirements. Thus, a deeper understanding of product advertisement with reference to consumer sentiments and its implications need to be established. The current research depicts the contribution of artificial intelligence to analyze the consumers' attention, cognition, and emotion. The target product was Samsung Galaxy. Researcher of the current study has employed Think-aloud procedure for data analysis. Tweets dataset was divided into 2 categories. For international consumers' sentiments 30,877 tweets whereas for Pakistani consumers' sentiments tweets dataset was 26,834. For data analysis, authors used Nvivo for generating theme. The Nvivo produced word cloud. The word cloud generated with Pakistani tweets revealed that consumer attachment with Samsung product is based on emotional and attention and the preferred features of Samsung products are linked with emotional and attention. In contrary to that rest of the world tweets unfolded that emotion, attention, and cognition make consumer preferences while selecting Samsung products. This study is useful to the cellular companies for targeting across the world population. The consumer preference varies while selecting cell phones. This study will provide a better idea to cell phone companies for manufacturing consumer oriented cell phones to get better results. Moreover, future research should add more countries separate data and generate a comparative study between developed countries consumer and developing countries consumer preferences. In addition to companies with better insights of consumer can highlight the most attractive features of cell phone in their advertisements. [ABSTRACT FROM AUTHOR]

The study examined the development of Chinese as a second language learners' formulaic knowledge through comparing the processing of Chinese idioms versus non-idiomatic formulaic sequences (FSs) by advanced-level learners (ALs), super-advanced learners (SLs), and native speakers (NSs). Using two phrase acceptability judgment tasks with and without think-aloud protocols, we collected data on participants' processing accuracy, processing speed, and processing strategies of reading the two types of FSs. Four processing patterns emerged from the analyses of the datasets. First, learners' processing accuracy and speed increased along with their proficiency. Second, learners' idiom processing ability was generally lower than that of non-idiom processing ability, but they demonstrated an improving trend as their proficiency level increased. Third, learners' use of processing strategies did not change much as proficiency rose and demonstrated a categorical difference from NSs. Fourth, all three groups exhibited poorer productive idiom knowledge than productive non-idiom knowledge. The overall findings denote that second language learners' formulaic knowledge can evolve beyond the lexical plateau as learners move from the advanced to a higher proficiency level, but the productive idiom knowledge can be a long-term problem. The findings provide implications for measuring and teaching Chinese formulaic knowledge at the higher-than-advanced stage. [ABSTRACT FROM AUTHOR]

The study examined the development of Chinese as a second language learners’ formulaic knowledge through comparing the processing of Chinese idioms versus non-idiomatic formulaic sequences (FSs) by advanced-level learners (ALs), super-advanced learners (SLs), and native speakers (NSs). Using two phrase acceptability judgment tasks with and without think-aloud protocols, we collected data on participants’ processing accuracy, processing speed, and processing strategies of reading the two types of FSs. Four processing patterns emerged from the analyses of the datasets. First, learners’ processing accuracy and speed increased along with their proficiency. Second, learners’ idiom processing ability was generally lower than that of non-idiom processing ability, but they demonstrated an improving trend as their proficiency level increased. Third, learners’ use of processing strategies did not change much as proficiency rose and demonstrated a categorical difference from NSs. Fourth, all three groups exhibited poorer productive idiom knowledge than productive non-idiom knowledge. The overall findings denote that second language learners’ formulaic knowledge can evolve beyond the lexical plateau as learners move from the advanced to a higher proficiency level, but the productive idiom knowledge can be a long-term problem. The findings provide implications for measuring and teaching Chinese formulaic knowledge at the higher-than-advanced stage.

Despite the importance of effective observational analysis in coaching the technical aspects of climbing performance, limited research informs this aspect of climbing coach education. Thus, the purpose of the present research was to explore the feasibility and the utility of a novel methodology, combining eye tracking technology and cued retrospective think-aloud (RTA), to capture the cognitive–perceptual mechanisms that underpin the visual search behaviors of climbing coaches. An analysis of gaze data revealed that expert climbing coaches demonstrate fewer fixations of greater duration and fixate on distinctly different areas of the visual display than their novice counterparts. Cued RTA further demonstrated differences in the cognitive–perceptual mechanisms underpinning these visual search strategies, with expert coaches being more cognizant of their visual search strategy. To expand, the gaze behavior of expert climbing coaches was underpinned by hierarchical and complex knowledge structures relating to the principles of climbing movement. This enabled the expert coaches to actively focus on the most relevant aspects of a climber’s performance for analysis. The findings demonstrate the utility of combining eye tracking and cued RTA interviewing as a new, efficient methodology of capturing the cognitive–perceptual processes of climbing coaches to inform coaching education/strategies.

Despite the importance of effective observational analysis in coaching the technical aspects of climbing performance, limited research informs this aspect of climbing coach education. Thus, the purpose of the present research was to explore the feasibility and the utility of a novel methodology, combining eye tracking technology and cued retrospective think-aloud (RTA), to capture the cognitive–perceptual mechanisms that underpin the visual search behaviors of climbing coaches. An analysis of gaze data revealed that expert climbing coaches demonstrate fewer fixations of greater duration and fixate on distinctly different areas of the visual display than their novice counterparts. Cued RTA further demonstrated differences in the cognitive–perceptual mechanisms underpinning these visual search strategies, with expert coaches being more cognizant of their visual search strategy. To expand, the gaze behavior of expert climbing coaches was underpinned by hierarchical and complex knowledge structures relating to the principles of climbing movement. This enabled the expert coaches to actively focus on the most relevant aspects of a climber's performance for analysis. The findings demonstrate the utility of combining eye tracking and cued RTA interviewing as a new, efficient methodology of capturing the cognitive–perceptual processes of climbing coaches to inform coaching education/strategies. [ABSTRACT FROM AUTHOR]

Metacognition is typically measured by collecting self-reported information from participants while they complete a cognitive task. Recent evidence suggests that eliciting such metacognitive information from participants can impact both their metacognitive processes and their cognitive performance. Although there are contradictory findings regarding the magnitude and even the direction of this effect, recent evidence has converged to provide a clearer picture of the mechanisms that determine reactivity. Here, we provide a review of the evidence that measures of metacognition, namely think-aloud protocols, judgments of learning, and confidence ratings, are reactive. We argue that reactivity has important implications not just for the measurement of metacognition, but for metacognition theorizing because reactivity can provide insights into the cues participants use to monitor their performance. Drawing from this synthesis of evidence, we propose a tentative framework for studying reactivity that integrates cue processing accounts of reactivity with existing models of metacognition. We conclude the review by addressing some of the pertinent questions yet to be comprehensively addressed by reactivity research, including how researchers should best address issues of reactivity when using experimental designs.

Metacognition is typically measured by collecting self-reported information from participants while they complete a cognitive task. Recent evidence suggests that eliciting such metacognitive information from participants can impact both their metacognitive processes and their cognitive performance. Although there are contradictory findings regarding the magnitude and even the direction of this effect, recent evidence has converged to provide a clearer picture of the mechanisms that determine reactivity. Here, we provide a review of the evidence that measures of metacognition, namely think-aloud protocols, judgments of learning, and confidence ratings, are reactive. We argue that reactivity has important implications not just for the measurement of metacognition, but for metacognition theorizing because reactivity can provide insights into the cues participants use to monitor their performance. Drawing from this synthesis of evidence, we propose a tentative framework for studying reactivity that integrates cue processing accounts of reactivity with existing models of metacognition. We conclude the review by addressing some of the pertinent questions yet to be comprehensively addressed by reactivity research, including how researchers should best address issues of reactivity when using experimental designs. [ABSTRACT FROM AUTHOR]

Studies have examined the impact of distraction on basic task performance (e.g., working memory, motor responses), yet research is lacking regarding its impact in the domain of think-aloud cognitive assessment, where the threat to assessment validity is high. The Articulated Thoughts in Simulated Situations think-aloud cognitive assessment paradigm was employed to address this issue. Participants listened to scenarios under three conditions (i.e., while answering trivia questions, playing a visual puzzle game, or with no experimental distractor). Their articulated thoughts were then content-analyzed both by the Linguistic Inquiry and Word Count (LIWC) program and by content analysis of emotion and cognitive processes conducted by trained coders. Distraction did not impact indices of emotion but did affect cognitive processes. Specifically, with the LIWC system, the trivia questions distraction condition resulted in significantly higher proportions of insight and causal words, and higher frequencies of non-fluencies (e.g., uh or umm) and filler words (e.g., like or you know). Coder-rated content analysis found more disengagement and more misunderstanding particularly in the trivia questions distraction condition. A better understanding of how distraction disrupts the amount and type of cognitive engagement holds important implications for future studies employing cognitive assessment methods.

Studies have examined the impact of distraction on basic task performance (e.g., working memory, motor responses), yet research is lacking regarding its impact in the domain of think-aloud cognitive assessment, where the threat to assessment validity is high. The Articulated Thoughts in Simulated Situations think-aloud cognitive assessment paradigm was employed to address this issue. Participants listened to scenarios under three conditions (i.e., while answering trivia questions, playing a visual puzzle game, or with no experimental distractor). Their articulated thoughts were then content-analyzed both by the Linguistic Inquiry and Word Count (LIWC) program and by content analysis of emotion and cognitive processes conducted by trained coders. Distraction did not impact indices of emotion but did affect cognitive processes. Specifically, with the LIWC system, the trivia questions distraction condition resulted in significantly higher proportions of insight and causal words, and higher frequencies of non-fluencies (e.g., ?uh? or ?umm?) and filler words (e.g., ?like? or ?you know?). Coder-rated content analysis found more disengagement and more misunderstanding particularly in the trivia questions distraction condition. A better understanding of how distraction disrupts the amount and type of cognitive engagement holds important implications for future studies employing cognitive assessment methods. [ABSTRACT FROM AUTHOR]