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Using Multivariate Statistics

Social Learning and Clinical Psychology.

Part One: Initial Considerations Chapter 1: Motivation in Organizations Mitchell, Terence R., and Daniels, Denise. Observation and Commentary on Recent Research in Work Motivation. Chapter 2: Conceptual Approaches to Motivation at Work Ryan, Richard M., and Deci, Edward L. 2000. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1): 68-78. Mowday, Richard, and Colwell, Kenneth A. Employee reactions to unfair outcomes in the workplace: The contributions of Adams' equity theory to understanding work motivation. Cropanzano, Russell, and Rupp, Deborah. An overview of organizational justice: Implications for work motivation. Komaki, Judith. Reinforcement theory at work: Enhancing and explaining what employees do. Locke, Edwin A. 1996. Motivation through conscious goal setting. Applied and Preventive Psychology, 5: 117-124. Stajkovic, Alexander D., and Luthans, Fred. Social cognitive theory and self-efficacy: Implications for motivation theory and practice. Part Two: Central Issues in Motivation at Work Chapter 3: The Role of Cognitions, Beliefs, and Attitudes in Motivation Staw, Barry M. 1986. Organizational psychology and the pursuit of the happy/productive worker. California Management Review, 28(4): 40-53. Rousseau, Denise M., and Tijoriwala, Snehal A. 1999. What's a good reason to change? Motivated reasoning and social accounts in promoting organizational change. Journal of Applied Psychology, 84(4): 514-528. Luthans, Fred. Positive Organizational Behavior: Implications for Leadership and HR Development and Motivation. Chapter 4: The Role of Goals and Intentions in Motivation Klein, Howard J., Wesson, Michael J., Hollenbeck, John R., and Alge, Bradley J. 1999. Goal commitment and the goal-setting process: Conceptual clarification and empirical synthesis. Journal of Applied Psychology, 6: 885-896. O'Leary-Kelly, Anne M., Martocchio, Joseph J., and Frink, Dwight D. 1994. A review of the influence of group goals on group performance. Academy of Management Journal, 37(5): 1285-1301. Crown, Deborah F., and Rosse, Joseph G. 1995. Yours, mine, and ours: Facilitating group productivity through the integration of individual and group goals. Organizational Behavior and Human Decision Processes, 64(2): 138-150. Chapter 5: The Role of Affect in Motivation Raghunathan, Rajagopal, and Pham, Michel T. 1999. All negative moods are not equal: Motivational influences of anxiety and sadness on decision-making. Organizational Behavior and Human Decision Processes, 79(1): 56-77. Venkatesh, Viswanath, and Speier, Cheri. 1999. Computer technology training in the workplace: A longitudinal investigation of the effect of mood. Organizational Behavior and Human Decision Processes, 79(1): 1-28. Chapter 6: The Role of Social Influences in Motivation Porter, Lyman W., Lawler, Edward E. III, and Hackman, J. Richard. 1975. Ways groups influence individual effectiveness. (Holdover from previous edition) Vardi, Yoav and Wiener, Yoash. 1996. Misbehavior in organizations: A motivational framework. Organization Science, 7(2): 151-165. Whyte, Glen. 1998. Recasting Janis's groupthink model: The key role of collective efficacy in decision fiascoes. Organizational Behavior and Human Decision Processes, 73(2/3): 185-209. Chapter 7: The Role of Cross-Cultural Influences in Work Motivation Hofstede, G. 1993. Cultural constraints in management theories. Academy of Management Executive, 7(1): 81-94. Sanchez-Runde, Carlos J., and Steers, Richard M. Cultural influences on work motivation and performance. Frese, Michael, Kring, Wolfgang, Soos, Andrea, Zempel, Jeannette. 1996. Personal initiative at work: Differences between east and west Germany. Academy of Management Journal, 39(1): 37-63. Meek, Christopher B. 1999. Ganbatte: Understanding the Japanese employee. Business Horizons, January-February, 27-36. Chapter 8: The Role of Individual Differences in Motivation O'Reilly, Charles A. III and Chatman, Jennifer A. 1994. Working smarter and harder: A longitudinal study of managerial success. Administrative Science Quarterly, 39: 603-627. Pilegge, Anthony J. and Holtz, Rolf. 1997. The effects of social identity on the self-set goals and task performance of high and low self-esteem individuals. Organizational Behavior and Human Decision Processes, 70(1): 17-26. Part Three: Applications of Motivational Approaches Chapter 9: Rewards Lawler, Edward L. 1987. The design of effective reward systems. In J. W. Lorsch (ed.), Handbook of Organizational Behavior. Englewood Cliffs, NJ: Prentice Hall, pp, 25-271. Kerr, Steven. 1995. On the folly of rewarding A, while hoping for B. Academy of Management Executive, 9(1): 7-14. Pearce, Jone L. 1987. Why merit pay doesn't work: Implications from organizational theory. In D. B. Balkin and L. R. Gomez-Mejia (eds.), New Perspectives on Compensation, pp. 169-178. Pfeffer, Jeffrey. 1998. Six dangerous myths about pay. Harvard Business Review, May-June, 109-119. Duncan, W. Jack. 2001. Stock ownership and work motivation. Organizational Dynamics, 30(1): 1-11. Chapter 10: Punishment George, Jennifer M. 1995. Asymmetrical effects of rewards and punishments: the case of social loafing. Journal of Occupational and Organizational Psychology, 68: 327-338. Butterfield, Kenneth D., Trevino, Linda K., and Ball, Gail A. 1996. Punishment from the manager's perspective: A grounded investigation and inductive model. Academy of Management Journal, 39(6): 1479-1512. Chapter 11: Motivating Creativity aand Innovation Amabile, Teresa. 1997. Motivating creativity in organizations: On doing what you love and loving what you do. California Management Review, 40(1): 39-58. Cummings, Anne and Oldham, Greg R. 1997. Enhancing creativity: Managing work contexts for the high potential employee. California Management Review, 40(1): 22-38.

Motivatiom and work behaviour

The Psychology of Religion and Coping: Theory, Research, Practice

The Bergen Facebook Addiction Scale (BFAS), initially a pool of 18 items, three reflecting each of the six core elements of addiction (salience, mood modification, tolerance, withdrawal, conflict, and relapse), was constructed and administered to 423 students together with several other standardized self-report scales (Addictive Tendencies Scale, Online Sociability Scale, Facebook Attitude Scale, NEO-FFI, BIS/BAS scales, and Sleep questions). That item within each of the six addiction elements with the highest corrected item-total correlation was retained in the final scale. The factor structure of the scale was good (RMSEA = .046, CFI = .99) and coefficient alpha was .83. The 3-week test-retest reliability coefficient was .82. The scores converged with scores for other scales of Facebook activity. Also, they were positively related to Neuroticism and Extraversion, and negatively related to Conscientiousness. High scores on the new scale were associated with delayed bedtimes and rising times.

Development of a Facebook Addiction Scale.

The purpose of this study is to examine the relationships between internet addiction and depression, anxiety, and stress. Participants were 300 university students who were enrolled in mid-size state University, in Turkey. In this study, the Online Cognition Scale and the Depression Anxiety Stress Scale were used. In correlation analysis, internet addiction was found positively related to depression, anxiety, and stress. According to path analysis results, depression, anxiety, and stress were predicted positively by internet addiction. This research shows that internet addiction has a direct impact on depression, anxiety, and stress.

/pdf/internet-addiction-and-depression-anxiety-and-stress-1oglad9h13.pdf

Internet Addiction and Depression, Anxiety and Stress

The purpose of this research is to examine the relationship of internet addiction, social self-efficacy, and academic locus of control. Participants were 311 university students who completed a questionnaire package that included the Online Cognition Scale, the Academic Locus of Control Scale, and the Perceived Social Self-efficacy Scale. The hypothesis model was tested through structural equation modeling. According to results internal academic locus of control was predicted positively by social self-efficacy. Also internet addiction was explained negatively by social self-efficacy and internal academic locus of control and positively by external academic locus of control. Results were discussed in the light of literature.

Social self-efficacy, academic locus of control, and internet addiction

The aim of the present study is to examine the relationships between Internet addiction, subjective vitality, and subjective happiness. The participants were 328 university students who completed a questionnaire package that included the Online Cognition Scale, the Subjective Vitality Scale, and the Subjective Happiness Scale. According to the results, subjective vitality and subjective happiness were negatively predicted by Internet addiction. On the other hand, subjective happiness was positively predicted by subjective vitality. In addition, subjective vitality mediated the relationship between Internet addiction and subjective happiness. Results were discussed in light of the literature.

/pdf/the-relationships-between-internet-addiction-subjective-38pw3hsbz4.pdf

The relationships between Internet addiction, subjective vitality, and subjective happiness.

This study investigated the validity and reliability of the Turkish version of the Metacognitive Awareness Inventory. The sample of the study consisted of 607 university students. Results of language equivalence indicated that the correlations between Turkish and English forms of the MAI were quite high (r = .93). As a result of a series of factor analyses eight subscales have emerged under the knowledge and regulation of cognition. These subscales were declarative knowledge, procedural knowledge, conditional knowledge, planning, monitoring, evaluation, debugging, and information management. The internal consistency of the entire inventory was .95. The item-total correlations ranged from .35 to .65 and test-retest reliability coefficient was .95. According to these findings, the Metacognitive Awareness Inventory is a valid and reliable instrument that can be used in the field of education. Key Words Metacognitive Awareness, Validity, Reliability, Factor Analysis It is important for students to be aware of their strengths and limitations as learners. In last twenty years, metacognition has been receiving increased attention in cognitive psychology. Specific attention has been focused on this construct as the interface between cognition and affect and its essential role in self-regulation in achievement settings (Carrell, Gajdusek, & Wise, 1998; Lucangeli & Cornoldi, 1997). Metacognition itself does not predict achievement, but theorists believe that it may serve as a mediator to learning (Braten, 1991; Bruning, Schraw, & Ronning, 1995). Pintrich & De Groot, 1990). Highly metacognitive individuals do better than others in planning, managing information, monitoring, debugging, and evaluating (Anderson & Walker, 1991; Schraw & Dennison 1994). The concept of metacognition was introduced by John Flavell in the early 1970s, based on the term metamemory, previously conceived by the same scholar (Butler & Winne, 1995; Campbell, 1999; Delclos & Harrington, 1991). Flavell (1979) regarded metacognition as learners' knowledge of their own cognition, defining it as "knowledge and cognition about cognitive phenomena" (p. 906). Metacognition is often referred to in the literature as 'thinking about one's own thinking', or 'cognitions about cognitions'. It is usually associated with learners' knowledge, awareness, and control of the processes by which they learn (Brown 1987; Garner & Alexander 1989) and the metacognitive learner is believed to be characterized by ability to recognize, evaluate, and where needed reconstruct existing ideas (Blank, 2000; Gunstone, 1991; Wellman, 1985). Though no universally accepted definition of metacognition can be found in the literature, many researchers agree on common fundamental components of metacognition and they suggest that metacognition can be classified into two main components as; knowledge of cognition and regulation of cognition (Brown, 1987; Everson & Tobias, 1998; Flavell, 1987; Forrest-Pressley & Waller; 1984; Mazzoni & Nelson, 1998; Metcalfe & Shimmura, 1994; Nelson & Narens, 1990; Schraw & Dennison, 1994). Knowledge of cognition refers to what individuals know about their own cognition or about cognition in general (Kumar, 1998; Kyllonen & Woltz, 1989). It includes at least three different kinds of metacognitive awareness: Declarative, procedural, and conditional knowledge (Brown, 1987; Jacobs & Paris, 1987; Schraw & Moshman, 1995). Declarative knowledge refers to knowing "about" things. Procedural knowledge refers to knowing "how" to do things. Conditional knowledge refers to knowing the "why" and "when" aspects of cognition. Regulation of cognition refers to a set of activities that help students control their learning (Gavelek & Raphael, 1982; Gourgey, 1998; Hartman, 1998). Although a number of regulatory skills have been defined in the literature, three basic skills are included in all accounts: Planning, monitoring, and evaluation (Fraenkel & Wallen, 2000; Jacobs & Paris, 1987). …

The Validity and Reliability of the Turkish Version of the Metacognitive Awareness Inventory.

The aim of this study is to examine the relationships between chemistry laboratory anxiety, chemistry attitudes, and self-efficacy. Participants were 395 university students. Participants completed the Chemistry Laboratory Anxiety Scale, the Chemistry Attitudes Scale, and the Self-efficacy Scale. Results showed that chemistry laboratory anxiety was correlated negatively to chemistry attitudes and to self-efficacy. On the other hand, chemistry attitudes were found to be positively associated with self-efficacy. The path model showed that self-efficacy predicted chemistry laboratory anxiety in a negative way. Also, self-efficacy has a direct and positive effect on chemistry attitudes which in turn affects chemistry laboratory anxiety. Finally, chemistry laboratory anxiety was explained negatively by chemistry attitudes. Results were discussed in the light of literature.

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Ahmet Akin

Papers

Internet Addiction and Depression, Anxiety and Stress

Social self-efficacy, academic locus of control, and internet addiction

The relationships between Internet addiction, subjective vitality, and subjective happiness.

The Validity and Reliability of the Turkish Version of the Metacognitive Awareness Inventory.

The Relationships between University Students' Chemistry Laboratory Anxiety, Attitudes, and Self-Efficacy Beliefs