A Review of Psychometric Data Analysis and Applications in Modelling of Academic Achievement in Tertiary Education
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Big Five Predictors of Academic Achievement
Journal of Research in Personality 35, 78±90 (2001) doi:10.1006/jrpe.2000.2309, available online at http://www.idealibrary.com on Big Five Predictors of Academic Achievement Sampo V. Paunonen University of Western Ontario, London, Ontario, Canada and Michael C. Ashton Brock University, St Catharines, Ontario, Canada A large-sample study (N ϭ 717) is described in which two broad Big Five factor measures were compared with two narrow personality trait measures in the predic- tion of ®nal grades in an undergraduate psychology course. The Big Five factors evaluated as predictors were Conscientiousness and Openness to Experience (or Intellect). The traits evaluated, which were constituents of the respective factors, were need for Achievement and need for Understanding. In each comparison, the lower level trait measure did better than its higher level factor measure in the predic- tion of course grades. We conclude that the aggregation of narrow trait measures into broad factor measures can be counterproductive from the points of view of both behavior prediction and behavior explanation. 2001 Academic Press Some researchers believe that the variation in human behavior can be ade- quately summarized in terms of ®ve broad dimensions of personality. Those dimensions, known as the Big Five personality factors, are typically labeled as Extraversion, Agreeableness, Conscientiousness, Neuroticism (vs Emo- tional Stability), and Openness to Experience (or Intellect). The Big Five have been recovered in many studies and in many cultures, with the analysis of both comprehensive lists of personality-descriptive adjectives (e.g., De Raad, Perugini, HrebõÂckovaÂ, & Szarota, 1998) and numerous questionnaires comprising diverse personality trait scales (see McCrae & John, 1992). -
An Introduction to Psychometric Theory with Applications in R
What is psychometrics? What is R? Where did it come from, why use it? Basic statistics and graphics TOD An introduction to Psychometric Theory with applications in R William Revelle Department of Psychology Northwestern University Evanston, Illinois USA February, 2013 1 / 71 What is psychometrics? What is R? Where did it come from, why use it? Basic statistics and graphics TOD Overview 1 Overview Psychometrics and R What is Psychometrics What is R 2 Part I: an introduction to R What is R A brief example Basic steps and graphics 3 Day 1: Theory of Data, Issues in Scaling 4 Day 2: More than you ever wanted to know about correlation 5 Day 3: Dimension reduction through factor analysis, principal components analyze and cluster analysis 6 Day 4: Classical Test Theory and Item Response Theory 7 Day 5: Structural Equation Modeling and applied scale construction 2 / 71 What is psychometrics? What is R? Where did it come from, why use it? Basic statistics and graphics TOD Outline of Day 1/part 1 1 What is psychometrics? Conceptual overview Theory: the organization of Observed and Latent variables A latent variable approach to measurement Data and scaling Structural Equation Models 2 What is R? Where did it come from, why use it? Installing R on your computer and adding packages Installing and using packages Implementations of R Basic R capabilities: Calculation, Statistical tables, Graphics Data sets 3 Basic statistics and graphics 4 steps: read, explore, test, graph Basic descriptive and inferential statistics 4 TOD 3 / 71 What is psychometrics? What is R? Where did it come from, why use it? Basic statistics and graphics TOD What is psychometrics? In physical science a first essential step in the direction of learning any subject is to find principles of numerical reckoning and methods for practicably measuring some quality connected with it. -
The Influence of Paying Attention in Classroom on Students' Academic Achievement in Terms of Their Comprehension and Recall Ability
2-4 February 2015- Istanbul, Turkey 684 Proceedings of INTCESS15- 2nd International Conference on Education and Social Sciences THE INFLUENCE OF PAYING ATTENTION IN CLASSROOM ON STUDENTS’ ACADEMIC ACHIEVEMENT IN TERMS OF THEIR COMPREHENSION AND RECALL ABILITY Turkiya Al’Omairi1*, Husam Al Balushi2 1Ms. Assistant Lecturer, Sultanate of Oman, [email protected] 2Mr. English Teacher, Sultanate of Oman, [email protected]. * Corresponding Author Abstract Students' attention in classroom and their academic achievement are two related variables, and they are reflected in students' comprehension and recall ability. However, most of the studies referred to comprehension and recall ability interchangeably and mainly used recall tasks to measure working memory capacity. Adding to that, to the best of my knowledge, there are not many studies that combine the three main variables, but they relate each one of attention and working memory capacity to achievement in an indirect way. Thus, this paper was conducted to investigate whether paying attention in class affect students' academic achievement in terms of their comprehension and recall ability. In order to measure the three main variables, which are comprehension, recall ability and attention, three different tests were used, and they were applied on a sample of two hundred English Education students in counseling psychology class. The comprehension test had three questions related to the previous lesson of counselling psychology class. For the recall ability, a task had three parts, each of which included lists of pictures or letters that the participants needed to recall their order, and the attention task was mainly adapted from the Stroop colour naming task. -
Cluster Analysis for Gene Expression Data: a Survey
Cluster Analysis for Gene Expression Data: A Survey Daxin Jiang Chun Tang Aidong Zhang Department of Computer Science and Engineering State University of New York at Buffalo Email: djiang3, chuntang, azhang @cse.buffalo.edu Abstract DNA microarray technology has now made it possible to simultaneously monitor the expres- sion levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremen- dous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. Cluster analysis seeks to partition a given data set into groups based on specified features so that the data points within a group are more similar to each other than the points in different groups. A very rich literature on cluster analysis has developed over the past three decades. Many conventional clustering algorithms have been adapted or directly applied to gene expres- sion data, and also new algorithms have recently been proposed specifically aiming at gene ex- pression data. These clustering algorithms have been proven useful for identifying biologically relevant groups of genes and samples. In this paper, we first briefly introduce the concepts of microarray technology and discuss the basic elements of clustering on gene expression data. -
Reliability Engineering: Today and Beyond
Reliability Engineering: Today and Beyond Keynote Talk at the 6th Annual Conference of the Institute for Quality and Reliability Tsinghua University People's Republic of China by Professor Mohammad Modarres Director, Center for Risk and Reliability Department of Mechanical Engineering Outline – A New Era in Reliability Engineering – Reliability Engineering Timeline and Research Frontiers – Prognostics and Health Management – Physics of Failure – Data-driven Approaches in PHM – Hybrid Methods – Conclusions New Era in Reliability Sciences and Engineering • Started as an afterthought analysis – In enduing years dismissed as a legitimate field of science and engineering – Worked with small data • Three advances transformed reliability into a legitimate science: – 1. Availability of inexpensive sensors and information systems – 2. Ability to better described physics of damage, degradation, and failure time using empirical and theoretical sciences – 3. Access to big data and PHM techniques for diagnosing faults and incipient failures • Today we can predict abnormalities, offer just-in-time remedies to avert failures, and making systems robust and resilient to failures Seventy Years of Reliability Engineering – Reliability Engineering Initiatives in 1950’s • Weakest link • Exponential life model • Reliability Block Diagrams (RBDs) – Beyond Exp. Dist. & Birth of System Reliability in 1960’s • Birth of Physics of Failure (POF) • Uses of more proper distributions (Weibull, etc.) • Reliability growth • Life testing • Failure Mode and Effect Analysis -
Fatigue and Psychological Distress in the Working Population Psychometrics, Prevalence, and Correlates
Journal of Psychosomatic Research 52 (2002) 445–452 Fatigue and psychological distress in the working population Psychometrics, prevalence, and correlates Ute Bu¨ltmanna,*, Ijmert Kanta, Stanislav V. Kaslb, Anna J.H.M. Beurskensa, Piet A. van den Brandta aDepartment of Epidemiology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands bDepartment of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT, USA Received 11 October 2000 Abstract Objective: The purposes of this study were: (1) to explore the distinct pattern of associations was found for fatigue vs. relationship between fatigue and psychological distress in the psychological distress with respect to demographic factors. The working population; (2) to examine associations with demographic prevalence was 22% for fatigue and 23% for psychological and health factors; and (3) to determine the prevalence of fatigue distress. Of the employees reporting fatigue, 43% had fatigue only, and psychological distress. Methods: Data were taken from whereas 57% had fatigue and psychological distress. Conclusions: 12,095 employees. Fatigue was measured with the Checklist The results indicate that fatigue and psychological distress are Individual Strength, and the General Health Questionnaire (GHQ) common in the working population. Although closely associated, was used to measure psychological distress. Results: Fatigue was there is some evidence suggesting that fatigue and psychological fairly well associated with psychological distress. A separation -
When Psychometrics Meets Epidemiology and the Studies V1.Pdf
When psychometrics meets epidemiology, and the studies which result! Tom Booth [email protected] Lecturer in Quantitative Research Methods, Department of Psychology, University of Edinburgh Who am I? • MSc and PhD in Organisational Psychology – ESRC AQM Scholarship • Manchester Business School, University of Manchester • Topic: Personality psychometrics • Post-doctoral Researcher • Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh. • Primary Research Topic: Cognitive ageing, brain imaging. • Lecturer Quantitative Research Methods • Department of Psychology, University of Edinburgh • Primary Research Topics: Individual differences and health; cognitive ability and brain imaging; Psychometric methods and assessment. Journey of a talk…. • Psychometrics: • Performance of likert-type response scales for personality data. • Murray, Booth & Molenaar (2015) • Epidemiology: • Allostatic load • Measurement: Booth, Starr & Deary (2013); (Unpublished) • Applications: Early life adversity (Unpublished) • Further applications Journey of a talk…. • Methodological interlude: • The issue of optimal time scales. • Individual differences and health: • Personality and Physical Health (review: Murray & Booth, 2015) • Personality, health behaviours and brain integrity (Booth, Mottus et al., 2014) • Looking forward Psychometrics My spiritual home… Middle response options Strongly Agree Agree Neither Agree nor Disagree Strong Disagree Disagree 1 2 3 4 5 Strongly Agree Agree Unsure Disagree Strong Disagree -
Biostatistics (BIOSTAT) 1
Biostatistics (BIOSTAT) 1 This course covers practical aspects of conducting a population- BIOSTATISTICS (BIOSTAT) based research study. Concepts include determining a study budget, setting a timeline, identifying study team members, setting a strategy BIOSTAT 301-0 Introduction to Epidemiology (1 Unit) for recruitment and retention, developing a data collection protocol This course introduces epidemiology and its uses for population health and monitoring data collection to ensure quality control and quality research. Concepts include measures of disease occurrence, common assurance. Students will demonstrate these skills by engaging in a sources and types of data, important study designs, sources of error in quarter-long group project to draft a Manual of Operations for a new epidemiologic studies and epidemiologic methods. "mock" population study. BIOSTAT 302-0 Introduction to Biostatistics (1 Unit) BIOSTAT 429-0 Systematic Review and Meta-Analysis in the Medical This course introduces principles of biostatistics and applications Sciences (1 Unit) of statistical methods in health and medical research. Concepts This course covers statistical methods for meta-analysis. Concepts include descriptive statistics, basic probability, probability distributions, include fixed-effects and random-effects models, measures of estimation, hypothesis testing, correlation and simple linear regression. heterogeneity, prediction intervals, meta regression, power assessment, BIOSTAT 303-0 Probability (1 Unit) subgroup analysis and assessment of publication -
Big Data for Reliability Engineering: Threat and Opportunity
Reliability, February 2016 Big Data for Reliability Engineering: Threat and Opportunity Vitali Volovoi Independent Consultant [email protected] more recently, analytics). It shares with the rest of the fields Abstract - The confluence of several technologies promises under this umbrella the need to abstract away most stormy waters ahead for reliability engineering. News reports domain-specific information, and to use tools that are mainly are full of buzzwords relevant to the future of the field—Big domain-independent1. As a result, it increasingly shares the Data, the Internet of Things, predictive and prescriptive lingua franca of modern systems engineering—probability and analytics—the sexier sisters of reliability engineering, both statistics that are required to balance the otherwise orderly and exciting and threatening. Can we reliability engineers join the deterministic engineering world. party and suddenly become popular (and better paid), or are And yet, reliability engineering does not wear the fancy we at risk of being superseded and driven into obsolescence? clothes of its sisters. There is nothing privileged about it. It is This article argues that“big-picture” thinking, which is at the rarely studied in engineering schools, and it is definitely not core of the concept of the System of Systems, is key for a studied in business schools! Instead, it is perceived as a bright future for reliability engineering. necessary evil (especially if the reliability issues in question are safety-related). The community of reliability engineers Keywords - System of Systems, complex systems, Big Data, consists of engineers from other fields who were mainly Internet of Things, industrial internet, predictive analytics, trained on the job (instead of receiving formal degrees in the prescriptive analytics field). -
Psycholinguistic Research Methods 251
Psycholinguistic Research Methods 251 See also: Deixis and Anaphora: Pragmatic Approaches; Freud S (1915). ‘Die Verdra¨ngung.’ In Gesammelte Werke Jakobson, Roman (1896–1982); Lacan, Jacques (1901– X. Frankfurt am Main: Imago. 1940–1952. 1981); Metaphor: Psychological Aspects; Metonymy; Lacan J (1955–1956). Les Psychoses. Paris: Seuil, 1981. Rhetoric, Classical. Lacan J (1957). ‘L’instance de la lettre dans l’inconscient ou la raison depuis Freud.’ In E´ crits. Paris: Seuil, 1966. Lacan J (1957–1958). Les formations de l’inconscient. Bibliography Paris: Seuil, 1998. Lacan J (1959). ‘D’une question pre´liminaire a` tout traite- Freud S (1900). ‘Die Traumdeutung.’ In Gesammelte werke ment possible de la psychose.’ In E´ crits. Paris: Seuil, II-III. Frankfurt am Main: Imago. 1940–1952. 1966. Freud S (1901). ‘Zur Psychopathologie des Alltagslebens.’ Lacan J (1964). Les quatre concepts fondamentaux de la In Gesammelte werke IV. Frankfurt am Main: Imago. psychanalyse. Paris: Seuil, 1973. 1940–1952. Lacan J (1969–1970). L’envers de la psychanalyse. Paris: Freud S (1905). ‘Der Witz und seine Beziehung zum Unbe- Seuil, 1991. wussten.’ In Gesammelte Werke, VI. Frankfurt am Main: Imago. 1940–1952. Psycholinguistic Research Methods S Garrod, University of Glasgow, Glasgow, UK This usually involves taking the average of the values ß 2006 Elsevier Ltd. All rights reserved. of the dependent variable (response latencies) for each value of the independent variable (each list of words acquired at different ages) and establishing Psycholinguistics aims to uncover the mental repre- whether the differences associated with the different sentations and processes through which people pro- values of the independent variable are statistically duce and understand language, and it uses a wide reliable. -
JEROME SEYMOUR BRUNER COURTESY of RANDALL FOX 1 October 1915
JEROME SEYMOUR BRUNER COURTESY OF RANDALL FOX 1 october 1915 . 5 june 2016 PROCEEDINGS OF THE AMERICAN PHILOSOPHICAL SOCIETY VOL. 161, NO. 4, DECEMBER 2017 biographical memoirs s a student of narrative, Jerome (Jerry) Seymour Bruner knew well that one can tell many stories about an individual person, Aevent, and life. Indeed, at the start of his autobiography, Jerry Bruner wrote, “I can find little in [my childhood] that would lead anybody to predict that I would become an intellectual or an academic, even less a psychologist.” And yet, it is appropriate—if not essential—to begin this memoir with the fact that Jerry Bruner was born blind. Only at age 2, after two successful cataract operations (Jerry spoke of “good luck and progress in ophthalmology”) could Jerry see. For the rest of his lengthy and event-filled life, he wore memorably thick corrective lenses. And when he was not peering directly at you—be you an audience of one or of one thousand—he would grasp his glasses firmly in his palm and punctuate his fluent speech with dramatic gestures. As a younger child of an affluent Jewish family living in the suburbs of New York City, Jerry was active, playful, and fun-loving—not partic- ularly intellectual or scholarly. His sister Alice wondered why he was always asking questions; Jerry later quipped that he was “trying out hypotheses.” Freud said that the death of a father is the most important event in a man’s life. Whether or not cognizant of this psychoanalytic pronouncement, Bruner seldom referred to his mother; he devoted much more space in his autobiography and much more time in conver- sation to commemorating his father: “Everything changed, collapsed, after my father died when I was twelve, or so it seemed to me.” And indeed, as he passed through adolescence and into early adulthood, Bruner became a much more serious student, a budding scholar, a wide-ranging intellectual. -
Harry Harlow, John Bowlby and Issues of Separation
Integr Psych Behav (2008) 42:325–335 DOI 10.1007/s12124-008-9071-x INTRODUCTION TO THE SPECIAL ISSUE Loneliness in Infancy: Harry Harlow, John Bowlby and Issues of Separation Frank C. P. van der Horst & René van der Veer Published online: 13 August 2008 # The Author(s) 2008. This article is published with open access at Springerlink.com Abstract In this contribution, the authors give an overview of the different studies on the effect of separation and deprivation that drew the attention of many in the 1940s and 1950s. Both Harlow and Bowlby were exposed to and influenced by these different studies on the so called ‘hospitalization’ effect. The work of Bakwin, Goldfarb, Spitz, and others is discussed and attention is drawn to films that were used to support new ideas on the effects of maternal deprivation. Keywords Separation . Maternal deprivation . Hospitalization effect . History of psychology. Attachment theory . Harlow. Bowlby From the 1930s through the 1950s clinical and experimental psychology were dominated by ideas from Freud’s psychoanalytic theory and Watson’s behaviorism. Although very different in their approach to the study of (human) behavior, psychoanalysts and behaviorists held common views on the nature of the bond between mother and infant. According to scientists from both disciplines the basis for this relationship was a secondary drive, i.e. the fact that the child valued and loved the mother was because she reduced his or her primary drive for food. The central figure of this special issue, American animal psychologist Harry Harlow (1905–1981), in the 1950s shifted his focus from studies of learning in monkeys (e.g., Harlow and Bromer 1938; Harlow 1949) to a more developmental approach—or in Harlow’s own words a transition “from learning to love” (cf.