The role of answer fluency and perceptual fluency in the monitoring and control of reasoning: Reply to Alter, Oppenheimer, and Epley

In this reply, we provide an analysis of Alter et al. (2013) response to our earlier paper (Thompson et al., 2013). In that paper, we reported difficulty in replicating Alter, Oppenheimer, Epley, and Eyre’s (2007) main finding, namely that a sense of disfluency produced by making stimuli difficult to perceive, increased accuracy on a variety of reasoning tasks. Alter, Oppenheimer, and Epley (2013) argue that we misunderstood the meaning of accuracy on these tasks, a claim that we reject. We argue and provide evidence that the tasks were not too difficult for our populations (such that no amount of “metacognitive unease” would promote correct responding) and point out that in many cases performance on our tasks was well above chance or on a par with Alter et al.’s (2007) participants. Finally, we reiterate our claim that the distinction between answer fluency (the ease with which an answer comes to mind) and perceptual fluency (the ease with which a problem can be read) is genuine, and argue that Thompson et al. (2013) provided evidence that these are distinct factors that have different downstream effects on cognitive processe

Comparing Mental Effort, Difficulty, and Confidence Appraisals in Problem-Solving: A Metacognitive Perspective

It is well established in educational research that metacognitive monitoring of performance assessed by self-reports, for instance, asking students to report their confidence in provided answers, is based on heuristic cues rather than on actual success in the task. Subjective self-reports are also used in educational research on cognitive load, where they refer to the perceived amount of mental effort invested in or difficulty of each task item. In the present study, we examined the potential underlying bases and the predictive value of mental effort and difficulty appraisals compared to confidence appraisals by applying metacognitive concepts and paradigms. In three experiments, participants faced verbal logic problems or one of two non-verbal reasoning tasks. In a between-participants design, each task item was followed by either mental effort, difficulty, or confidence appraisals. We examined the associations between the various appraisals, response time, and success rates. Consistently across all experiments, we found that mental effort and difficulty appraisals were associated more strongly than confidence with response time. Further, while all appraisals were highly predictive of solving success, the strength of this association was stronger for difficulty and confidence appraisals (which were similar) than for mental effort appraisals. We conclude that mental effort and difficulty appraisals are prone to misleading cues like other metacognitive judgments and are based on unique underlying processes. These findings challenge the accepted notion that mental effort appraisals can serve as reliable reflections of cognitive load

Identifying globally relevant learnings from Africa’s challenges and solutions to climate change and air pollution-related health impacts: a data science scoping review protocol

Introduction Leveraging data science could significantly advance the understanding of the health impacts of climate change and air pollution to meet health systems’ needs and improve public health in Africa. This scoping review will aim to identify and synthesise evidence on the use of data science as an intervention to address climate change and air pollution-related health challenges in Africa.Methods and analysis The search strategy will be developed, and the search will be conducted in the Web of Science, Scopus, CAB Abstracts, MEDLINE and EMBASE electronic databases. We will also search the reference lists of eligible articles for additional records. We will screen titles, technical reports, abstracts and full texts and select studies reporting the use of data science in relation to the health effects and interventions associated with climate change and air pollution in Africa.Ethics and dissemination There are no formal ethics requirements as we are not collecting primary data. Results, once published, will be disseminated via conferences and shared with policy-makers and public health, air pollution and climate change key stakeholders in Africa

Identifying globally relevant learnings from Africa’s challenges and solutions to climate change and air pollution-related health impacts: a data science scoping review protocol

Peer reviewed: TrueAcknowledgements: We thank the National Institute for Health, Global Institute for Health Studies, Fogarty Division of International Science Policy, Planning and Evaluation and its partner organizations for initiating this project.IntroductionLeveraging data science could significantly advance the understanding of the health impacts of climate change and air pollution to meet health systems’ needs and improve public health in Africa. This scoping review will aim to identify and synthesise evidence on the use of data science as an intervention to address climate change and air pollution-related health challenges in Africa.Methods and analysisThe search strategy will be developed, and the search will be conducted in the Web of Science, Scopus, CAB Abstracts, MEDLINE and EMBASE electronic databases. We will also search the reference lists of eligible articles for additional records. We will screen titles, technical reports, abstracts and full texts and select studies reporting the use of data science in relation to the health effects and interventions associated with climate change and air pollution in Africa.Ethics and disseminationThere are no formal ethics requirements as we are not collecting primary data. Results, once published, will be disseminated via conferences and shared with policy-makers and public health, air pollution and climate change key stakeholders in Africa.</jats:sec