Teaching Structured Analytical Thinking with Data Using Visual–Analytic Tools

Author(s):  
Guoray Cai
Keyword(s):  
Author(s):  
Bastien Trémolière ◽  
Marie-Ève Gagnon ◽  
Isabelle Blanchette

Abstract. Although the detrimental effect of emotion on reasoning has been evidenced many times, the cognitive mechanism underlying this effect remains unclear. In the present paper, we explore the cognitive load hypothesis as a potential explanation. In an experiment, participants solved syllogistic reasoning problems with either neutral or emotional contents. Participants were also presented with a secondary task, for which the difficult version requires the mobilization of cognitive resources to be correctly solved. Participants performed overall worse and took longer on emotional problems than on neutral problems. Performance on the secondary task, in the difficult version, was poorer when participants were reasoning about emotional, compared to neutral contents, consistent with the idea that processing emotion requires more cognitive resources. Taken together, the findings afford evidence that the deleterious effect of emotion on reasoning is mediated by cognitive load.


2019 ◽  
Vol 34 (2) ◽  
pp. 23-39 ◽  
Author(s):  
Elizabeth V. Grace ◽  
Ashley Davis

ABSTRACT This instructional case encourages analytical thinking about internal controls in both the operations and audit of a small, not-for-profit organization. Students examine a control environment characterized by unauthorized expenditures, lack of documentation, and missing documents. Using the COSO (2013) framework, students demonstrate understanding of business processes as they identify internal control risks and deficiencies, and recommend control improvements. Auditing students additionally apply management assertions about financial transactions and assess auditor independence. Students gain practical experience in developing flowcharts of accounting processes and writing a management letter for a familiar organization: a preschool.


2019 ◽  
Vol 34 (7) ◽  
pp. 1459-1467 ◽  
Author(s):  
Sherese Y. Duncan ◽  
Raeesah Chohan ◽  
João José Ferreira

Purpose This paper aims to explore, using the employee lens of business-to-business firms, word use through brand engagement and social media interaction to understand the difference between employees who rate their employer brands highly on social media and those who don't. Design/methodology/approach We conducted a textual content analysis of posts published on the social media job evaluation site glassdoor.com. LIWC software package was used to analyze 30 of the top 200 business-to-business brands listed on Brandwatch using four variables, namely, analytical thinking, clout, authenticity and emotional tone. Findings The results show that employees who rate their employer’s brand low use significantly more words, are significantly less analytic and write with significantly more clout because they focus more on others than themselves. Employees who rate their employer’s brand highly, write with significantly more authenticity, exhibit a significantly higher tone and display far more positive emotions in their reviews. Practical implications Brand managers should treat social media data disseminated by individual stakeholders, like the variables used in this study (tone, word count, frequency), as a valuable tool for brand insight on their industry, competition and their own brand equity, now and especially over time. Originality/value This study provides acknowledgement that social media is a significant source of marketing intelligence that may improve brand equity by better understanding and managing brand engagement.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Francisco Benita ◽  
Darshan Virupaksha ◽  
Erik Wilhelm ◽  
Bige Tunçer

AbstractThis paper proposes an Internet of Things device (IoT)-based ecosystem that can be leveraged to provide children and adolescent students with STEM educational activities. Our framework is general and scalable, covering multi-stakeholder partnerships, learning outcomes, educational program design and technical architecture. We highlight the importance of bringing Data-driven Thinking to the core of the learning environment as it leads to collaborative learning experience and the development of specific STEM skills such as problem-finding and solving, cognitive, analytical thinking, spatial skills, mental manipulation of objects, organization, leadership, management, and so on. A successful case study in Singapore involving tens of thousands of students is presented.


2021 ◽  
Vol 11 (6) ◽  
pp. 289
Author(s):  
Jaime Huincahue ◽  
Rita Borromeo-Ferri ◽  
Pamela Reyes-Santander ◽  
Viviana Garrido-Véliz

School is a space where learning mathematics should be accompanied by the student’s preferences; however, its valuation in the classroom is not necessarily the same. From a quantitative approach, we ask from the mathematical thinking styles (MTS) theory about the correlations between preferences of certain MTS and mathematical performance. For this, a valid test instrument and a sample of 275 16-year-old Chilean students were used to gain insight into their preferences, beliefs and emotions when solving mathematical tasks and when learning mathematics. The results show, among other things, a clear positive correlation between mathematical performance and analytical thinking style, and also evidence the correlation between self-efficacy, analytical thinking and grades. It is concluded that students who prefer the analytical style are more advantageous in school, since the evaluation processes have a higher valuation of analytic mathematical thinking.


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