• Users Online: 77
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 

 Table of Contents  
ORIGINAL ARTICLE
Year : 2015  |  Volume : 1  |  Issue : 1  |  Page : 36-42

Need for cognition and training reaction: The mediating role of learning motivation


Department of Psychology, Educational Sciences and Psychology Faculty, University of Isfahan, Isfahan, Iran

Date of Web Publication19-Dec-2014

Correspondence Address:
Farzaneh Dabbashi
Department of Psychology, Educational Sciences and Psychology Faculty, University of Isfahan, Isfahan
Iran
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2395-2296.147468

Rights and Permissions
  Abstract 

Aim: This study was conducted to investigate the relationship of need for cognition and training reaction while considering the mediating role of learning motivation. Methods: The design of the research was correlational and Statistical population consisted total of trainees of the entrepreneurship center of the University of Isfahan. The sample was selected by applying cluster random sampling and was consisted 164 people of these trainees that were measured in tow-phases (pretraining and posttraining). Used questionnaires of the research were Cacioppo, Petty and Kao's scale of need for cognition (1984), and Noe and Wilk's learning motivation questionnaire (1993) and researcher-made training reaction. The indirect effects were tested using the Bootstrap procedure in Preacher and Hayes's macro program (2004). Results: Results demonstrated that between the need for cognition, learning motivation, training reaction and its three-dimension (reaction to training content, reaction to trainer and reaction to course plan) there are significant positive relationships. Furthermore, learning motivation mediated the relationship between need for cognition and training reaction and its dimensions, too. Discussion: With attention to the findings of this research, we recommend to responsible of training that pay specific attention to need for cognition and learning motivation, and improve these two variables in training programs.

Keywords: Learning motivation, need for cognition, training, training reaction and its dimension


How to cite this article:
Dabbashi F, Oreyzi H, Nouri A, Akrami N. Need for cognition and training reaction: The mediating role of learning motivation. Int J Educ Psychol Res 2015;1:36-42

How to cite this URL:
Dabbashi F, Oreyzi H, Nouri A, Akrami N. Need for cognition and training reaction: The mediating role of learning motivation. Int J Educ Psychol Res [serial online] 2015 [cited 2017 Nov 22];1:36-42. Available from: http://www.ijeprjournal.org/text.asp?2015/1/1/36/147468


  Introduction Top


It seems that nowadays everyone knows the importance and value of research in the field of training. Because the modern age is improving with a high pace, and all the evidences show that this pace will increase in the future. [1] The rapid and continuous changes in the labor market due to technology changes, gradual changes, market liberation rules and also the growth in job demanding, sensitize the urgent of noticing the role of training system in nurturing the self-employed graduates. Such role proposes commitments for training system. [2] The policymakers believe that accessing to the high levels of training is possible just through entrepreneurship training. [3] Such these trainings give learners the chance of testing and proving their ideas and opinions before entering them in real labor world. [4]

By noticing the vital importance of training, especially entrepreneur training and low rate of returning asset that is spent for such trainings, [5] both training designers and researchers are interested in recognition of factors that influence success and effectiveness of training programs.

A study of the history of evaluation and effectiveness of training show that till now various approaches have noted different factors for specifying the effectiveness of training courses. For example, Spector thinks that kind of training is effective that achieves the predetermined goals, while Ashridge thinks the one that has been edited and performed based on training standards. [6] However, the first attempts for presenting a comprehensive pattern for evaluation and the effectiveness of trainings related to job have been started by Kirkpatrick in 1959 and 1960. Based on Kirkpatrick's four-level-evaluation model, the first level -which is one of the most important levels of training evaluation-, is the level of reaction to training. Reaction to training refers to the learners' feelings toward the training program. [7] The other levels of this pattern are learning, behavior, and results, respectively. One of the basic assumptions of this pattern is that there is a hierarchical and causality relation among these tetra levels of training evaluation. Based on this assumption, training leads to reaction, and reaction leads to learning. In the same order, learning leads to change in behavior and training transfer to performance. [8] Next assumption is that there is a positive relationship between evaluation levels. The results of some of the researches support this assumption. [9],[10]

In this research, assessment of relationship between this variable and its dimensions with need for cognition, and also the study of the mediation role of learning motivation in this relationship has been noted by emphasizing on importance of reaction to training level in evaluation and effectiveness of training processes.

The need for cognition is defined as "the need for arranging situations related to meaning and methods for coordination of information, the need for knowing and rationalizing life experiences." [11] The Cohen's aim by using the word "need" is not the one that is used in biological texts for starvation, thirst, and the other biological needs, rather, in his opinion we can regard this concept as a kind of interest and tendency for removing scientific need, that is, a behavior that is purposeful and when the purpose seems to be unreachable it can cause tension in individual. [12] Petty and Cacioppo (1986) call these purposeful acts, the rational processing of messages. Researchers have understood that individuals, who are in a high level with respect to need for cognition, have a natural tendency toward searching for more information for understanding the world. They have a spontaneous motivation for dealing with cognitive activities. [13]

A lot of researches imply the potential role of need for cognition in specifying the learning outcomes. For example, some researches have shown that the need for cognition has a significant positive relationship with attempt, enjoying and performing training duties. [13],[14],[15],[16] Researches also imply this issue that the need for cognition could have relationships with dimensions of training reaction. For example, Cacioppo et al., found out that the need for cognition influences the trainer's perception. [17] Besides, some researches have shown the meaningful relations between the need for cognition and training outcomes. For example Woo et al. found out a median significant relationship between need for cognition, self-regulation in learning and individuals' declarative knowledge. [18] Elias and Loomis found out in their research that the need for cognition has a relationship with training self-efficacy and the mean of student's score and it could be a significant predictor for training performances. [19]

Despite significance of these relationships, we can't ignore the role of learning motivation in training performances. Since a lot of researches imply the mediation role of learning motivation in the relationship between individual characteristics and training outcomes. [20] Training or learning motivation is an important and impressive variable in training outcomes and includes processes that cause activation, direction and consistency of behavior. [21] A lot of researches confirm the relationship between individual factors and training motivation [22] and training motivation with training outcomes. [23] Besides, several researches have shown that learning motivation can perform as a mediator variable in the relationship between individual's characteristics and training outcomes. [20],[22],[23] Nonetheless, there is not any research that has been done about the mediation role of training motivation in a relationship between need for cognition and training outcomes. So the examination of this issue helps us to understand these relationships better.

Regarding to importance of training reaction and its dimensions in training effectiveness, and with considering the influences of need for cognition on training outcomes, and also attention to important role of learning motivation between trainers' individual characteristics and training outcomes; the main purpose of this research is specifying the relationship between need for cognition and training reaction and also need for cognition with every dimension of training reacting and considering the mediating role of learning motivation [Figure 1].
Figure 1: Research proposed model about the indirect effect of need for cognition on training reaction through learning motivation (model 1)

Click here to view


Besides this main hypothesis, inferior hypotheses are examined too which notice the mediation role of learning motivation in relationship between need for cognition and sub-scales of training reaction (reaction to training content, reaction to trainer and reaction to training design), [Figure 2], [Figure 3], [Figure 4].
Figure 2: Research proposed model about the indirect effect of need for cognition on reaction to training content through learning motivation (model 2)

Click here to view
Figure 3: Research proposed model about the indirect effect of need for cognition on reaction to trainer through learning motivation (model 3)

Click here to view
Figure 4: Research proposed model about the indirect effect of need for cognition on reaction to training design through learning motivation (model 4)

Click here to view


So the hypotheses of this research have been arranged as follows:

  • Need for cognition can predict the training motivation (path a)
  • Learning motivation can predict training reaction and its sub-scales (including reaction to training content, reaction to trainer and reaction to training design) (paths b1 to b4)
  • Need for cognition can predict training reaction and its sub-scales (including reaction to training content, reaction to trainer and reaction to training design) (paths c1 to c4)
  • There is no significant relationship between need for cognition and training reaction and its sub-scales after controlling learning motivation (Paths c`1 to c`4).



  Methods Top


Participants and research design

The design of this research was correlational and statistical population were all of the participants in short-term courses of the University of Isfahan's entrepreneurship center. The sampling was based on random clustered and was chosen from individuals who were participating in short-term courses held in the University of Isfahan's entrepreneurship center in fall 2012 and winter 2013. In training researches due to its nature, all the members of one cluster are usually examined. In this research, the expectation cluster was chosen between fall 2012 and winter 2013, and in two phases (pretraining and posttraining) they answered to research tools. 200 pairs of questionnaires were sent which by considering the rate of return 0.82, 164 pairs of questionnaire were returned. The titles of entrepreneurship center's training courses were: Business plan, branding, knowledge management, and exchange. The common feature of all of these courses is that by providing the conditions for improving knowledge, skill, attitude and self-efficacy in trainees, we can provide a probability of training transfer to performance. The mean of participants' age was 24.57 and the standard deviation of their age was 5/861 and including 39% men and 61% female. The level of their educations was 45.1% B.A., 51.2% M.A., and 3.7% PhD, respectively.

Research tools

Included two types of questionnaires.

The questionnaires of pretraining research phase were: Cacioppo, Petty and Kao's need for cognition scale (1984) and Neo and Wilk's learning motivation questionnaire (1993).

The questionnaire of posttraining research phase was: Reaction to training researcher-made questionnaire.

The role of each variable in the research: Need for cognition was independent variable, learning motivation was mediator variable, and training reaction (in model 1), reaction to training content (in model 2), reaction to trainer (in model 3) and reaction to training design (in model 4) were dependent variables.

Need for the cognition questionnaire (Cacioppo, Petty and Kao, 1984)

This questionnaire was extracted from the Cacioppo, Petty and Kao's 18-items scale need for cognition (1984) [17] and is the shortened form of its 9-items one. These nine items of main scale have been extracted in a way that has the most consistency with entrepreneurship centers trainees' situation, and also to avoid asking similar questions. In this questionnaire, every item is scored in a 7 Likert's degree spectrum (0 = I'm disagree a lot to 6 = I'm agree a lot). Several studies showed evidences indicating the validity of this questionnaire. [17],[24] Cacioppo et al. (1984) have reported the reliability of this scale as 0.09 by using the Kronbakh's Alpha. In this research the reliability of this shortened form by using the Kronbakh's Alpha is 0.75. One of the items of this questioner is: "I find it especially satisfying to complete an important task that required a lot of thinking and mental effort."

Learning motivation questionnaire (Noe and Wilk, 1993)

This questionnaire has been extracted from Noe and Wilk's scale of learning motivation (1993) and has 8 items. [25] Every item is scored based on the 5 Likert's degree spectrum (1 = I disagree a lot to 5 = I disagree a lot). Several studies have shown evidences indicating the validity of this questionnaire. [25],[26] Noe and Wilk have reported the reliability of this scale as 0.87 by calculating the Kronbakh's Alpha. In other studies, Spiroz (2003) and Bakhtiari Esfandaghe (2011) have reported the Kronbakh's Alpha Factor as 0.81 and 0.86 for this scale, respectively. In this research the reliability for this questionnaire is 0.70 by using the Kronbakh's Alpha. One of the items of this questioner is: "The learning of all of the contents of this course is important for me."

Training reaction questionnaire (researcher-made)

This questionnaire has 39 questions and has been made based on the researches of Warr and Bunce, Morgan and Casper, Lee and Pershing and Sekowesky about the dimensions of reaction to training. [27],[28],[29],[30] This questionnaire examines three-dimension of reaction to training content, reaction to trainer and reaction to training design. At first this questionnaire was performed on a sample of participants in an elementary study, then factor analysis was done on data and the findings confirmed the existence of these three factors in questionnaire (KMO = 0.728). The researcher asked the following sentence which the main goal of the construct is based on it to examine the validity coefficient of this questionnaire (what is the level of your overall satisfaction about this training) and examined its correlation coefficient with whole scale that was 0.641. In this research, the reliability of this scale was calculated based on the Kronbakh's Alpha and that was 0.91. One of the items of this questioner is: "Trainer was capable of delivering of the training materials."

Method of executive and data analysis

As what was mentioned before, the questionnaires were distributed and collected in two periodical phases pretraining phase and immediately posttraining phase. The data were analyzed by Pearson's correlation coefficient. Besides, in order to studying the hypotheses related to the mediation relationships, Baron and Kenny's defaults (1986) were examined. Baron and Kenny mentioned that when the M variable is assumed as mediation that:

  • The variance of X (independent variable) predicts the variance of M and is significant, and the variance of M predicts the variance of Y (dependent variable) with control M and is significant [Figure 1], [Figure 2], [Figure 3], [Figure 4], a.b ≠ 0]
  • The variance of X predict the variance of Y and is significant [Figure 1], [Figure 2], [Figure 3], [Figure 4], c ≠ 0],
  • When M are controlled, the relationship between X and Y decreases or becomes not significant. [31]
In Preacher and Hayes's macro program (2004) Bootstrap procedure was used for specifying the significance of indirect paths of independent variable over dependent variables via mediator variable. In Preacher and Hayes's procedure (2004), besides the significance of Baron and Kenny's 3 required regressions, we use the Bootstrap procedure and its confidence interval (CI) resulted from it that evaluates the mediation role in a direct path. In Bootstrap procedure in order to measure the indirect effect of independent variable, by mediation variable over dependent variable at least thousands of samples are tested randomly and in every resampling, the amount of indirect effect is calculated. The quantity of indirect effects is ordered from the smallest amounts to the largest ones. If in the expecting CI, the up level and low level of the indirect effect are not zero; the researcher's hypothesis is confirmed based on the indirect effect of independent variable through mediation variable on dependent variables. [32] So for evaluating patterns 1-4 in this research, the Preacher and Hayes's Macro Program that was manufactured by Preacher and Hayes (2004). [33]


  Results Top


The results of participant's demographical characteristics were explained in the previous section. In [Table 1], descriptive and psychometric indexes of the research variables are shown, and in [Table 2] the internal correlation between the research variables are given.
Table 1: Descriptive and psychometric indexes of the research variables

Click here to view
Table 2: Coefficient correlation between the research variables

Click here to view


As shown in [Table 2], the need for cognition has significant and positive relationship with learning motivation, training reaction and all of its three-dimension including reaction to training content, reaction to trainer and reaction to training design (P < 0.05 and P < 0.01). Hence, the research hypotheses about relationships between need for cognition, and the other research variables are confirmed. Training reaction also has significant relationships with itself sub-scales (P < 0.01) and learning motivation has significant positive relationships with training reaction and its dimensions (P < 0.01).

In [Table 3], the direct and general effects of the research variables that are required for each of the mediation analysis are given. In this table we can evaluate the 3 required defaults that Baron and Kenny thought to be required for specifying mediating role.
Table 3: The direct and general effect of the research variables

Click here to view


As you see in [Table 3], the need for cognition with the standard coefficient 0.33 is able to predict the learning motivation and is significant (P < 0.01), so the condition of significance of path a for each of the mediation analysis is exists. besides, the learning motivation with the standard coefficients 0.40 (P < 0.01), 0.36 (P < 0.01), 0.26 (P < 0.01) and 0.35 (P < 0.01), can predict training reaction, reaction to training content, reaction to trainer, and reaction to training design, respectively. So the condition of significance of path b for each of the mediation analysis exists, too [Figure 1], [Figure 2], [Figure 3], [Figure 4], a.b ≠ 0]. Moreover, the results show that the need for cognition with the standard coefficients 0.23 (P < 0.01), 0.19 (P < 0.05), 0.20 (P < 0.01) and 0.16 (P < 0.05), is able to predict training reaction, reaction to training content, reaction to trainer and reaction to training design, respectively. So, the condition of significance of path c for each of the mediation analysis exists, too [Figure 1], [Figure 2], [Figure 3], [Figure 4], c ≠ 0]. Besides, as you see in [Table 3], when the effect of learning motivation in relationship between the need for cognition and training reaction and its sub-scales is controlled, the standard coefficients decrease to 0.11, 0.08, 0.13 and 0.05 respectively (c' paths), and lose their significance. So the third required condition of Baron and Kenny (1986) is existing, too.

The normal distribution test and Bootstrap procedure by Preacher and Hayes's macro program (2004) are used for examining the 1-4 models and significance of the indirect effects. The results of the normal distribution test and bootstrap procedure has been shown in [Table 4].
Table 4: The results of the normal distribution test and bootstrap procedure for the 1 - 4 models

Click here to view


The results of the normal distribution test in [Table 4] shows that the zero hypotheses based on the nullity of the indirect effect is rejected in each of the 4 expected models. Also the results of bootstrap procedure with the amount of 5000 resampling shows that neither in the 0.95% CI nor 0.99% CI, zero won't be between the low level and up level of none of the presented models, so the indirect path is significant in all of these four models. Based on these results, the learning motivation has a mediating role in relationship between the need for cognition and training reaction and the 3 its sub-scales (reaction to training content, reaction to trainer and reaction to training design).

Regarding this point that is based on the results of [Table 3] the c' path is not significant and based on the results of [Table 4], the indirect path is significant in normal distribution test and Bootstrap procedure. So, the learning motivation in all of these 4 presented models had the full mediating role, and all of the four presented models are confirmed.


  Discussion and Conclusion Top


This research was carried out by the purpose of the study of the relationships between need for cognition and training reaction and also its sub-scales, and examination of the mediating role of learning motivation. The research findings illustrate this point that the need for cognition has positive significant relationship with learning motivation. This finding means that by increasing need for cognition, learning motivation is increased too and vice versa. This finding is in harmony with the results of previous researches. [12],[13] These researchers found out that when people are in a higher level of need for cognition, they enjoy more from mental involving in challenging tasks, and they always choose the situations that reduce their intellectual tensions. Since entrepreneurship trainings have topics and contents beyond the formally taught lessons in university, attract people with cognitive curiosity and motivate their tendency for learning. The Jenkin's four-dimensional model (1979) presents this justification in explaining the relationships of cognition and metacognition with learning motivation; since learners are aware of their selves' cognitive weak and strong points, they usually motivate to use the particular strategic skills for dominating in training challenges. [34]

Also, the findings show that the need for cognition has positive significant relationships with training reaction and its sub-scales. These findings are harmonic with the findings of previous researches. [16],[17] Cacioppo et al. found out that the need for cognition influences the trainees' perception about trainer. These researchers discovered that the training content has an active role in it. [17] Researchers believe that people who are in a high level in the area of need for cognition have more focus on the message content which is the result of tending to perceive the world. [13]

The findings supported the main hypothesis that was about the mediating role of learning motivation in relationships between need for cognition and training reaction. This finding is in harmony with the findings of Quinones, Colquit and Simmering and Chuang et al. researches based on the mediating role of learning motivation in the relationships between individual characteristics and training outcomes. [20],[22],[23] Meanwhile there was not find any research that in particular studied the existence of mediating role of learning motivation between need for cognition and reaction to training that the comparison could not be done with the finding of this research.

At one point, there is a significant relationship between need for cognition and learning motivation both from theoretical aspect (Jenkin's four-dimensional pattern, 1979) and empirical one, [12],[13] and from the other point, a lot of researches have shown that there is a relationship between learning motivation and training reaction, [9],[23],[35] so can say that the need for cognition influences the learning motivation and this motivation causes learners to show desirable reactions to training, training content, trainer and training design. Since learning motivation was a full mediator in relationship between need for cognition and training reaction (and its sub-scales), can say that if there is no learning motivation, need for cognition cannot influence emotions toward training, trainer, training design and training content.

Regarding the findings of this research and by considering this subject that need for cognition and motivation is promotionable and improvable, we can expect that by designing training programs based on these two variables, trainees' feelings and reactions toward training improved, and based on Kirkpatrick's model (1976), learning and training transfer to performance happens in the next steps. We are suggested to future researchers that enter other cognitive and motivational variables and even individual variables into training research and by examining the used learning principles in these trainings, help to understanding of effectiveness and ways of its promotion in entrepreneurship trainings. Moreover, recommend to training designers both academic formal and entrepreneurship training to notice the metacognition aspects more and also try to identify more the different aspects of entrepreneurship to students and creating learning motivation on them.

This research has two main restrictions: First, all of the trainees attract to entrepreneurial training centers voluntarily. And second, these people have a little earlier knowledge about the content of teaching subjects that may influence their learning motivations. We can't ignore these two restrictions in this research and generalization must be done by regarding them.

 
  References Top

1.
Tai WT. Effects of training framing, general self-efficacy and training motivation on trainee's effectiveness. Pers Rev 2006;35:51-65.  Back to cited text no. 1
    
2.
Sedighi Pashaki A. The Study of Viewpoints Kardanesh Teachers and Students of Isfahan High School of Applying Elements Kardanesh Curriculum for Entrepreneurship Education. Unpublished M. A Thesis. University of Isfahan; 2011.  Back to cited text no. 2
    
3.
Oosterbeek H, Van Praag M. The impact of Entrepreneur education on entrepreneurship skills and motivation. Eur Econ Rev 2010;54:442-54.  Back to cited text no. 3
    
4.
Montessory C. The Entrepreneurship High School Challenge. Northern Kentucky University`s Fifth Third Bank Entrepreneurship Institute; 2006.  Back to cited text no. 4
    
5.
Goldstein IL, Ford JK. Training in Organizations. 4 th ed. Belmont CA: Wadsworth; 2002.  Back to cited text no. 5
    
6.
Fathi K, Diba T. The Evaluation of the Effectiveness of Training Courses. Tehran: Aeezh; 2006.  Back to cited text no. 6
    
7.
Kirkpatrick DL. Evaluation. In: Craig RL, editor. Training and Development Handbook. New York: McGraw-Hill; 1976.  Back to cited text no. 7
    
8.
Alliger GM, Janak EA. Kirkpatrick's levels of training criteria: Thirty years later. Pers Psychol 1989;42:331-42.  Back to cited text no. 8
    
9.
Esfandaghe FB. The Relationship Among Individual, Training and Organizational Characteristics and Training Outcomes in Isfahan Gas Company: A Proposed Training Evaluation and Effectiveness Model. Unpublished Ph.D. Thesis. University of Isfahan; 2011.  Back to cited text no. 9
    
10.
McKeachie WJ. Students ratings: The validity of use. Am Psychol 1997;52:1218-25.  Back to cited text no. 10
    
11.
Cohen AR, Stotland E, Wolfe DM. An experimental investigation of need for cognition. J Abnorm Psychol 1955;51:291-4.  Back to cited text no. 11
    
12.
Cacioppo JT, Petty RE. The need for cognition. J Pers Soc Psychol 1982;42:116-31.  Back to cited text no. 12
    
13.
Casioppo JT, Petty RE, Feinstein JA, Jarvis WG. Dispositional differences in cognitive motivation: The life and times of individuals varying in need for cognition. Psychol Bull 1996;119:197-253.  Back to cited text no. 13
    
14.
Baugh BT, Mason SE. Need for cognition related to time perception. Percept Mot Skills 1986;62:540-2.  Back to cited text no. 14
    
15.
Dornic S, Ekehammar B, Laaksonen T. Tolerance for mental effort: Self-ratings related to perception, performance, and personality. Pers Individ Dif 1991;12:313-9.  Back to cited text no. 15
    
16.
Sadowski CJ, Gulgoz S. Association of need for cognition and course performance. Percept Mot Skills 1992;74:498.  Back to cited text no. 16
    
17.
Cacioppo JT, Petty RE, Kao CF. The efficient assessment of need for cognition. J Pers Assess 1984;48:306-7.  Back to cited text no. 17
    
18.
Woo SE, Harms NR, Kuncel NR. Integrating personality and intelligence: Typical intellectual engagement and need for cognition. Pers Individ Dif 2007;43:1635-9.  Back to cited text no. 18
    
19.
Elias SM, Loomis RJ. Utilizing need for cognition and perceived self-efficacy to predict academic performance. J Appl Soc Psychol 2002;32:1687-702.  Back to cited text no. 19
    
20.
Quinones MA. Pretraining context effects: Training assignment as feedback. J Appl Psychol 1995;80:226-36.  Back to cited text no. 20
    
21.
Naylor JC, Pritchard RD, Ilgen DR. A Theory of Behavior in Organizations. Orlando, FI: Academic; 1980.  Back to cited text no. 21
    
22.
Colquitt JA, Simmering MJ. Conscientiousness goal orientation, and motivation to learn during the learning process: A longitudinal study. J Appl Psychol 1998;83:654-65.  Back to cited text no. 22
    
23.
Chuang A, Liao WC, Tai WT. An investigation of individual and contextual factors influencing training variables. Soc Behav Pers 2005;33:159-74.  Back to cited text no. 23
    
24.
Tuten TL, Bosnjak M. Understanding differences in web usage: The role of need for cognition and the five factor model of personality. Soc Behav Pers 2001;29:391-8.  Back to cited text no. 24
    
25.
Noe RA, Wilk SL. Investigation of the factors that influence employees' participation in development activities. J Appl Psychol 1993;78:291-302.  Back to cited text no. 25
    
26.
Spiros RK. Individual Difference in Motivation During Distance Training: The Influence of Goal Orientation and Self-Efficacy on Learning Outcomes. Unpublished Doctoral Disseration. Washington University; 2003.  Back to cited text no. 26
    
27.
Warr P, Bunce D. Trainee characteristics and the outcomes of open learning. Pers Psychol 1995;48:347-75.  Back to cited text no. 27
    
28.
Morgan RB, Casper W. Examining the factor structure of participant reactions to training: A multi-dimensional approach. Hum Resour Dev Q 2001;11:301-17.  Back to cited text no. 28
    
29.
Lee SH, Pershing JA. Effective reaction evaluation in evaluating training programs. Perform Improv 1999;38:32-9.  Back to cited text no. 29
    
30.
Sekowesky GJ. Evaluating Training Outcome Criteria. Unpublished Doctoral Dissertation. DePaul: University of DePaul; 2002.  Back to cited text no. 30
    
31.
Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986;51:1173-82.  Back to cited text no. 31
    
32.
Rezaei F, Nouri A, Oreyzi HR. Workplace incivility and turnover intention: The mediating role of organizational justice. J Knowl Res Appl Psychol 2012;12:40-9.  Back to cited text no. 32
    
33.
Preacher KJ, Hayes AF. SPSS and SAS procedures for estimating indirect effectsin simple mediation models. Behav Res Methods 2004;36:717-31.  Back to cited text no. 33
    
34.
Short EJ, Weissberg-Benchell JA. The triple alliance for learning: Cognition, Metacognition, and motivation. In: McCormic CB, editor. Cognitive Strategy Research New York: Springer-Verlag; 1989. p. 33-45.  Back to cited text no. 34
    
35.
Tracey B, Hinkin TR, Tannenbaum SI, Mathieu JE. The influence of individual characteristics and the work environment on varying levels if training outcomes. Hum Resour Dev Q 2001;12:5-23.  Back to cited text no. 35
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Methods
Results
Discussion and C...
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed1321    
    Printed45    
    Emailed0    
    PDF Downloaded175    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]