Estimates of Validity and Reliability for the Hemispheric Mode Indicator

1997 ◽  
Vol 85 (3_suppl) ◽  
pp. 1355-1364 ◽  
Author(s):  
Steve E. Hartman ◽  
Jaime Hylton

Concurrent validity of scores of the Hemispheric Mode Indicator (a measure of cognitive hemispheric dominance) was assessed by product-moment correlation with scores for the Human Information Processing Survey (a more-studied measure of hemispheric dominance) for 27 nurse-anesthetist students and 94 medical students ( r = .61 and .69, respectively). For 70 of the medical students, test-retest stability was only fair ( r = .74). For 525 undergraduates and 156 medical students, although alpha coefficients were .78 and .84, respectively, consideration of interitem correlations and principal components analyses indicated that some of the Hemispheric Mode Indicator's items are unsuitable as worded and that the 32 items probably represent more than one underlying latent variable.

2017 ◽  
Vol 4 (2) ◽  
Author(s):  
Dr. Rajesh Ganesan ◽  
Pankaj Singh

Mathematics Anxiety is an irrational fear of Mathematics. Mathematics Anxiety is defined as “the presence of a syndrome of emotional reactions to arithmetic and mathematics” (Dreger & Aiken, 1957, p.344). It creates a feeling of tension, apprehension, or fear that interferes with performance in Mathematics and also results in ‘Mathematics-Avoidance’. Further, ‘Mathematics-Avoidance’ leads to less competency, exposure and practice of Mathematics, leaving students more anxious and mathematically, unprepared to achieve. Math anxiety is a learned response that inhibits cognitive performance in the math classroom. It is widespread among students from elementary age through college. Students suffering from math anxiety have difficulty performing calculations and maintaining a positive outlook on mathematics. Math anxiety is the result of a cycle of math avoidance that begins with negative experiences regarding mathematics. These students avoid Mathematic courses and tend to feel negative towards Mathematics and this also affects student’s overall confidence level. However, Behaviour Modification techniques have proven instruments that can reduce various types of anxieties and Super Brain Yoga for improving integration of the brain. This is a case study of a student of IX standard, Kendriya Vidalaya, Who was referred by his Mathematics teacher and parent complaining that the student becomes anxious whenever he encounters Mathematic problems. After taking Math autobiography it was revealed that the anxiety began due to harsh handling by father while teaching Mathematics. Students score in recent Mathematic exam was noted very low i.e 12/40. His Mathematics Anxiety was assessed by using Suri, Monroe and Koc’s (2012) short Mathematics Anxiety Rating Scale. Student’s hemispheric dominance of the brain was measured by using Taggart and Torrance’s Human Information Processing Survey (1984). This student was treated with Behaviour Modification techniques and Super Brain Yoga for six weeks. Interventions used are: (i) Reduction of Rate of Breathing (Ganesan, 2012). (ii) Jacobson Progressive Muscle Relaxation (Jacobson, 1938) (iii) Laughter Technique (Ganesan, 2008b). (iv) Develpoment of Alternate Emotional Responses to the Threatening Stimulus (Ganesan, 2008a). (v) Super Brain Yoga (Sui, 2005). The anxiety level and performance in Mathematics exam was reassessed after six weeks. Results showed that Mathematics Anxiety was significantly reduced (60 to 20, 40%) and he performed better in the Mathematics exam (12/40 to 24/40, 30%). After reassessing student on Human Information Processing Survey by Taggart and Torrance (1984), it was found that student’s dominant information processing mode was ‘Integrated’ and this shows that Behaviour Modification techniques and Super Brain Yoga are efficient in treating Mathematics Anxiety.


1986 ◽  
Vol 58 (3) ◽  
pp. 823-830 ◽  
Author(s):  
Alice Kienholz ◽  
John Hritzuk

59 students in architecture and 50 medical students were compared using two questionnaire-defined measures of cognitive style. The Inquiry Mode Questionnaire (InQ) measured cognitive style according to five major dimensions: synthesist, idealist, analyst, realist and pragmatist. Your Style of Learning and Thinking (SOLAT)—Form C, now published as the Human Information Processing Survey (HIP Survey), measured preference for one of three main styles: a visuospatial, nonlinear, holistic, right-brain style; a verbal, analytic, sequential, left-brain style; and an integrated style involving an integration of the right and left styles. Significant differences were found for the two groups on the two questionnaires. Students in architecture favored the idealist style on the InQ and right-brain style on the SOLAT. Medical students favored the realist style on the InQ and the left-brain style on the SOLAT. Association between the InQ synthesist-idealist combined scores and the SOLAT inferred right-brain style and between the InQ analyst-realist style and the SOLAT left-brain style were observed.


2012 ◽  
Vol 28 (1) ◽  
pp. 60-67 ◽  
Author(s):  
Katariina Salmela-Aro ◽  
Katja Upadaya

This study introduces the Schoolwork Engagement Inventory (EDA), which measures energy, dedication, and absorption with respect to schoolwork. Structural equation modeling was used to assess the validity and reliability of the inventory among students attending postcomprehensive schools. A total of 1,530 (769 girls, 761 boys) students from 13 institutions (six upper-secondary and seven vocational schools) completed the EDA 1 year apart. The results showed that a one-factor solution had the most reliability and fitted best among the younger students, whereas a three-factor solution was most reliable and fit best among the older students. In terms of concurrent validity, depressive symptoms and school burnout were inversely related, and self-esteem and academic achievement were positively associated with EDA. Boys and upper-secondary-school students experienced lower levels of schoolwork engagement than girls and vocational-school students.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ozan Karaca ◽  
S. Ayhan Çalışkan ◽  
Kadir Demir

Abstract Background It is unlikely that applications of artificial intelligence (AI) will completely replace physicians. However, it is very likely that AI applications will acquire many of their roles and generate new tasks in medical care. To be ready for new roles and tasks, medical students and physicians will need to understand the fundamentals of AI and data science, mathematical concepts, and related ethical and medico-legal issues in addition with the standard medical principles. Nevertheless, there is no valid and reliable instrument available in the literature to measure medical AI readiness. In this study, we have described the development of a valid and reliable psychometric measurement tool for the assessment of the perceived readiness of medical students on AI technologies and its applications in medicine. Methods To define medical students’ required competencies on AI, a diverse set of experts’ opinions were obtained by a qualitative method and were used as a theoretical framework, while creating the item pool of the scale. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were applied. Results A total of 568 medical students during the EFA phase and 329 medical students during the CFA phase, enrolled in two different public universities in Turkey participated in this study. The initial 27-items finalized with a 22-items scale in a four-factor structure (cognition, ability, vision, and ethics), which explains 50.9% cumulative variance that resulted from the EFA. Cronbach’s alpha reliability coefficient was 0.87. CFA indicated appropriate fit of the four-factor model (χ2/df = 3.81, RMSEA = 0.094, SRMR = 0.057, CFI = 0.938, and NNFI (TLI) = 0.928). These values showed that the four-factor model has construct validity. Conclusions The newly developed Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS) was found to be valid and reliable tool for evaluation and monitoring of perceived readiness levels of medical students on AI technologies and applications. Medical schools may follow ‘a physician training perspective that is compatible with AI in medicine’ to their curricula by using MAIRS-MS. This scale could be benefitted by medical and health science education institutions as a valuable curriculum development tool with its learner needs assessment and participants’ end-course perceived readiness opportunities.


2007 ◽  
Vol 26 (3) ◽  
pp. 157-172
Author(s):  
Ivan P. Vaghely ◽  
Pierre-André Julien ◽  
André Cyr

Using grounded theory along with participant observation and interviews the authors explore how individuals in organizations process information. They build a model of human information processing which links the cognitivist-constructionist perspective to an algorithmic-heuristic continuum. They test this model using non-parametric procedures and find interesting results showing links to efficient information processing outcomes such as contributions to decision-making, knowledge-creation and innovation. They also identify some elements of best practice by efficient human information processing individuals whom they call the “information catalysts”.


2007 ◽  
Vol 10 (6) ◽  
pp. A455 ◽  
Author(s):  
L Scalone ◽  
G Cavrini ◽  
S Broccoli ◽  
F Borghetti ◽  
B Pacelli ◽  
...  

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