Relationship Between Personality Characteristics of Online Instructors and Student Evaluations



Tina G. Allen
Kaplan University
TAllen@Kaplan.edu

David B. Starnes
Kaplan University
DStarnes@Kaplan.edu

Robert E. Lockwood
Kaplan University
RLockwood@Kaplan.edu


Abstract


The purpose of this study was to examine the relationship between each of the five personality factors in the Big Five Inventory (BFI) and online faculty student evaluations. Faculty members from the School of Criminal Justice (CJ) and the School of Information Technology (IT) from an online university were asked to complete the BFI (44 item personality inventory). There were 179 valid BFI surveys returned with matched student evaluation data. There were small correlations between some of the five factors and student evaluations for all subjects. However, when separated by school, there were no statistically significant correlations for faculty in IT but there were significant correlations with moderate effect sizes for faculty in CJ.

Keywords: Big Five Inventory, Student Evaluations, Online Instructors

Relationship Between Personality Characteristics of Online Instructors and Student Evaluations

The way business operates is changing significantly. The evolving global workforce and technology have created new ways to improve efficiency, lower cost, and tap expertise. We now operate in the world of virtual teams, virtual contract employees, and a virtual workforce. According to the Bureau of Labor Statistics, in May 2004, over 20 million workers reported working part of the time from home (2005). With advances in technology, the boundaries between work and home continue to shrink for many workers. While these advances were thought to make workers more efficient the fact that workers, both traditional and virtual, are constantly available via email, smart phones, and other technologies provides challenges to all workers. The increase in telecommuting, home-based businesses, and virtual workers is creating changes in traditional work arrangements (Kreiner, Hollensbe, & Sheep, 2009). Because of the evolving workforce and technology the attributes considered for hiring used by today's employers differs greatly from that of employers before the advent of the virtual workforce.

There may be advantages and disadvantages for both the employer and the employee in the virtual workplace. Cascio (2000) reports one advantage is an increase in productivity. He cites an internal IBM study that showed gains of 15% to 40% in productivity. A potential disadvantage to the employee would be the lack of rapid and reliable technical assistance which is critical to success. Without immediate assistance it may be that independence and problem solving are necessary traits for successful employees. Another possible disadvantage for employees in a virtual workplace is the potential for feelings of isolation. Therefore, employees who are less subject to feelings of isolation may be more likely to succeed (Cascio, 2000). 

It is likely that a different set of skills is needed to succeed in an online work environment. The nuance of non-verbal cues is gone; as is simple team building activities such as visiting during breaks and meals. Furthermore, spontaneity may be lost because the need to plan for conversations increases to assure efficiency. Since virtual workers may be located all over the world, attention must even be paid to time zones when scheduling live or synchronous communications (Cascio, 2000).

Knoll and Jarvenpaa (1996) identified three key areas of virtual behavior: virtual-collaborative skills, virtual-socialization skills, and virtual-communication skills. Cascio (2000) built on this work and suggested that managers of virtual teams focus on these three behaviors as a way to enhance a team's ability to function effectively. Of particular importance a decade later are the virtual-communication skills. A worker's ability to communicate effectively influences both how they collaborate in a timely fashion and how they socialize or interact with colleagues virtually. In today's digital world, virtual communication skills involve more than sending and responding to email. Virtual workers must rely on several means of communicating including teleconferences, web conferences, and instant messaging/chat technologies. These changes in workplace communication may require employees with different personality characteristics to be successful.

The identification of characteristics required for success in the traditional workplace has been an area of inquiry for years. Several studies have linked employee characteristics to job performance showing that optimism (Jenson, Luthans, Lebsack, & Lebsack, 2007), explanatory style (Seligman & Schulman, 1986), undergraduate GPA (Lavinga, 1992), cognitive ability (Behling, 1998); Hunter & Hunter, 1984), core self-evaluations (Judge & Bono, 2001; Judge, Locke, Durham, & Kluger, 1998), emotional intelligence (Carmeli, 2003; Vakola, Tsaousis & Nikolaou, 2004), work orientation and interpersonal orientation (Day & Silverman, 1989), proactiveness (Seibert, Crant & Kraimer, 1999; Seibert, Kraimer, & Crant, 2001), personality (Bowling, 2007) are related to job performance. While many traits may be equally effective in the traditional face-to-face environment and in the virtual workplace, others may not. The critical question is what traits are most critical for success in the online environment?

The personality traits needed for success as an online college instructor have not been thoroughly researched. With the explosion of technology and internet resources, the increased popularity of online courses requires instructors to make extensive changes in their teaching strategies (Johnson, 2008; Diekelmann, Schuster, & Nosek, 1998). The limited real time communication, the absence of physical cues from students, and the inability to use gestures and other visual aids may require different personality traits for an online teacher to be effective.

This research sought to identify those personal characteristics that are related to high performing online instructors, as defined by perceptions of students completing end-of-term evaluations. Student evaluations of instructors are used by up to 85% of colleges and universities as one component of faculty evaluation, while some rely on student evaluations as their sole method of instructor evaluation (Patrick, 2011). Therefore, student evaluations may play a large role in awarding tenure, merit pay, and promotion for instructors.

The Big Five Dimensions of Personality

Digman (1990), in a review of personality structure traced the 60-year evolution of five personality constructs, which he referred to as the "Big Five". Digman found that regardless of the investigator, the conclusion was the same, "the domain could be adequately described by five superordinate constructs" (p. 420). The Big Five Constructs (BFC) of personality are: (1) Extraversion/Introversion, (2) Friendliness/Hostility/(or Agreeableness), (3) Conscientiousness (or Will), (4) Neuroticism/Emotional Stability and (5) Intellect/Openness (John, Naumann, & Soto, 2008; John, Donahue, & Kentle, 1991; Benet-Martinez & John, 1998 and Srivastava, (2012). For the purpose of this study it is important to note that Digman's meta-analysis supported the five-factor model and its usefulness in identifying the broad characteristics or traits of individual personalities (1990). Subsequent research also used these five constructs in a number of contexts, with many of them using the BFC as drivers of job satisfaction. In this research the BFC are investigated as they relate to student perceptions of instructor job performance in an online academic environment.

Past research provides mixed results suggesting that conscientiousness is a necessary but not sufficient condition for job success. Barrack and Mount (1991), investigated the relationship of the BFC to job proficiency. The results indicated that conscientiousness was the most prominent and consistent construct across the five occupational groups (professionals, police, managers, sales, and skilled/semi-skilled) included in the study. In a study of managers, Barrack and Mount (1993), determined that the characteristics of conscientiousness and extraversion were significantly related to job performance.

Hurtz & Donovan (2000) conducted a meta-analysis of the relationship between the BFC and job performance across occupations in various categories including sales, customer service, managers, and skilled/semiskilled. From this meta-analysis they concluded that conscientiousness was moderately related to job performance across all categories, but the other four traits may be important for consideration in certain occupations and should continue to be investigated. Salgado (1997) reported that a meta-analysis of studies conducted in the European community found that conscientiousness and emotional stability were valid predictors across occupations, but the remaining factors were valid for only some criteria and occupational groups.

Seibert & Kraimer (1999) studied 490 alumni from undergraduate business and engineering programs and MBA graduates of a private university. They found that extraversion was positively related to career success, salary, and promotions; however conscientiousness, in contrast to the findings of Hurtz & Donovan (2000), was not related to any career outcomes. In 2002, Witt, Burke, Barrick & Mount studied seven independent samples of employees from diverse occupations and found that employees who scored high on conscientiousness, but low on agreeableness, had lower performance ratings than those who were high on both constructs. However, the authors did caution employers on selecting employees based on conscientiousness alone.

Characteristics of Successful Virtual Employees

Several characteristics have been found to be associated with successful virtual employees. Internally motivated self-starters with strong technological skills were found more likely to be successful as virtual employees (Cascio, 2000). Michelle LaBrosse (2008), founder of Cheetah Learning, a virtual company with over 100 employees, contractors, and licensees worldwide maintains that passion is essential for success in the virtual workplace. Additionally, she maintained that self-starters, who do not require constant supervision, were found to perform best in the virtual environment. Thomas (2009) maintained that employees with high intrinsic reward systems do not require onsite supervision and thus might be more successful as virtual workers. Conlin (2009) reporting the findings of research conducted by Pearn Kandola (a psychological research-and-consulting company) for Cisco found that the extroverted and Type A personalities are better suited to virtual work and virtual workers have better organizational skills than their traditional office coworkers.

Characteristics of Effective Face-to-Face Instructors

Research on instructor effectiveness has focused on behaviors affecting students (Poplin & Sato-Hinman, 2006), communication styles (Hamann, Lineburgh, and Paul, 1998; Sidelinger & McCroskey, 1997), and personality characteristics such as self image (Combs, Blume, Newman, & Wass, 1974), confidence (Wasicsko 2002), belief systems (Wasicsko 2002) being positive (Krueger, 1997) and being sensitive, caring and nurturing (Cotton, 1995; Jenkins & Downs, 2001).

Communication styles have been studied extensively and communication styles that include energy, enthusiasm, and a high intensity level, reflect a positive attitude, and provide clarity have been found to be most effective (Hamann, Lineburgh, & Paul, 1998; Madsen, Standley & Cassidy, 1989; Sidelinger & McCroskey, 1997). Communication styles have also been linked to other characteristics, such as assertiveness, which was reported to be related to effectiveness (Sidelinger & McCroskey, 1997).

Effective instructors have been described as being caring and nurturing (Cotton, 1995). A caring instructor demonstrates a cooperative personality and an empathetic style while maintaining control. Instructors with a caring personality tend to have strong interpersonal skills and can handle discipline problems by being proactive and promoting a positive classroom environment (Roueche, Baker, Mullin, & Boy, 1986). Perry (1996) identified exemplary instructors from a student perspective as those who affirmed the value of the student, treated students with respect, helped students find relevance, and recognized potential situations that could impede student learning. Likewise, Marin Sánchez, Martinez-Pecino, Rodriguez, Melero (2011) found that students prefer instructors who are respectful, understanding and who are open to interaction.

Patrick (2011) examined student evaluations of teaching as they related to the Big Five Personality traits and expected final grades. This study asked students to complete two BFI questionnaires; one assessing themselves and another assessing their instructor. While instructors completed a self-assessed BFI, the results were not used due to a small sample size. The study included 176 students from only 5 instructors.  This study indicated that students favored extraversion, openness, agreeableness, and conscientiousness. Additionally, the author concluded that personality traits of the instructor, as perceived by the students, do affect their evaluations of the instructor.

Characteristics of Effective Online Instructors

Researchers have begun to pay attention to characteristics that make online instructors effective. While some skills and characteristics may be the same for both traditional and online, other characteristics and skills may be required for effective online instructors (Sixl-Daniell, Williams, & Wong 2006). Key findings include evidence that self-efficacy, confidence, enthusiasm and caring may be as important as skills and knowledge in determining online teacher effectiveness (Bauer & Kenton 2005; Rahman 2001). Edwards, Perry, and Janzen (2011) compared student perspectives of exemplary online and face-to-face instructors and found that exemplary instructors challenge and affirm students, establish classroom presence and serve to influence learners in a positive way. Effective online instructors have been described as having a persistent presence, promoting interaction, and building community (Cole, 2009). Young (2006) found that those online instructors who adapt to individual student needs, use meaningful examples, communicate effectively and indicate concern for students and their progress are more effective.

Method

This research sought to determine if there is a relationship between each of the five factors in the Big Five Inventory (BFI) (John, Donahue, & Kentle 1991; John, Naumann, & Soto 2008) and online faculty job performance as perceived by student evaluations. Faculty members in the School of Information Technology (IT) and School of Criminal Justice (CJ) for an online university were asked to complete the BFI. The five factors extracted from the 44 item inventory are (1) Extroversion, (2) Agreeableness, (3) Conscientiousness, (4) Neuroticism, and (5) Openness.

The end-of-term surveys completed by students include 5 positive statements related to instructor performance. The student evaluates the instructor on a scale from 1 (Strongly Disagree) to 5 (Strongly Agree). The five statements are: (1) The instructor demonstrated strong knowledge of the course content; (2) The instructor was prepared to teach this class; (3) The instructor actively engaged students with the course materials; (4) The instructor followed the syllabus during the term; and (5) Overall, the instructor was supportive of my success. From the five student evaluation statements the focus was on two of them, the instructor actively engaged students with the course materials and overall, the instructor was supportive of my success, as indicators of instructor effectiveness. The others are important but reflect more the instructors' conformance with faculty expectations.

To investigate the relationship between the BFI and student evaluations the Pearson Product Moment Correlations were calculated. Following this analysis Step-Wise Regression was employed to determine which personality factors or combination of personality factors may predict each of the two evaluation statements, engagement and support of student success. To the degree that specific personality factors are predictive of positive evaluations by students would provide support for the hypothesis under investigation in this study.

Results

There were 179 valid personality surveys (BFI) returned with student evaluation data, 119 from CJ and 60 from IT. Correlations were computed between each of the five personality factors and each of the five student evaluation statements. From the five student evaluation statements the two under investigation were "the instructor actively engaged students with the course materials" (Instructor Engagement) and "overall, the instructor was supportive of my success" (Overall Supportiveness). There were small relationships between four of the five personality factors and the two student evaluation statements for the 179 instructors in the combined group of CJ and IT. There were no significant correlations between the BFI factor of Extroversion and student evaluations.

Table 1: Bivariate Correlations between BFI Scales and Selected Teaching Measures

 

Instructor Engagement

Overall Supportiveness

BFI Extroversion

Pearson Correlation

.071

.043

Sig. (2-tailed)

.345

.570

N

179

179

BFI Agreeableness

Pearson Correlation

.230**

.202**

Sig. (2-tailed)

.002

.007

N

179

179

BFI Conscientiousness

Pearson Correlation

.283**

.164*

Sig. (2-tailed)

.000

.028

N

179

179

BFI Neuroticism

Pearson Correlation

-.238**

-.201**

Sig. (2-tailed)

.001

.007

N

179

179

BFI Openness

Pearson Correlation

.226**

.110

Sig. (2-tailed)

.002

.143

N

179

179

** Correlation is significant at the 0.01 level (2-tailed)
* Correlation is significant at the 0.05 level (2-tailed)

From Table 1 it can be seen that there were statistically significant correlations (α = .01) between the BFI factors of Agreeableness and Neuroticism with instructor engagement and with overall supportiveness. According to Cohen's (1988) conventions a correlation coefficient of .10 is thought to represent a weak or small association; a correlation coefficient of .30 is considered a moderate correlation; and a correlation coefficient of .50 or larger is thought to represent a strong or large correlation. Using these conventions, the effect sizes for these correlations were not sufficient to use in any meaningful prediction (Agreeableness: r2 = 0.05 and 0.04, Neuroticism: r2 = 0.05 and 0.04). There were also statistically significant correlations (α = .01) between the BFI factors of Conscientiousness and Openness and instructor engagement; but once again the effect sizes were not sufficient for use (Conscientiousness: r2 = 0.08 and Openness: r2 = 0.05).

To further investigate the correlation between these BFI factors of Agreeableness, Neuroticism, Conscientiousness, and Openness with instructor engagement and overall supportiveness the correlational analysis was conducted by school. As shown in Table 2, there were no statistically significant correlations between any of the personality factors with instructor engagement and overall supportiveness for faculty in the School of Information Technology; however, as shown in Table 3, there were statistically significant correlations (α = .01) between the BFI factors of Agreeableness, Neuroticism, Conscientiousness, and Openness with instructor engagement and overall supportiveness for faculty in the School of Criminal Justice.

Table 2: Bivariate Correlations between BFI Scales and Student Evaluations for Faculty in the School of Information Technology

 

Instructor Engagement

Overall Supportiveness

BFI Conscientiousness

Pearson Correlation

.084

-.078

Sig. (2-tailed)

.523

.553

N

60

60

BFI Extroversion

Pearson Correlation

.010

-.047

Sig. (2-tailed)

.938

.722

N

60

60

BFI Agreeableness

Pearson Correlation

.084

.151

Sig. (2-tailed)

.523

.250

N

60

60

BFI Neuroticism

Pearson Correlation

-.103

-.041

Sig. (2-tailed)

.435

.756

N

60

60

BFI Openness

Pearson Correlation

.045

-.116

Sig. (2-tailed)

.731

.376

N

60

60

 

Table 3: Bivariate Correlations between BFI Scales and Student Evaluations for Faculty in the School of Criminal Justice

 

Instructor Engagement

Overall Supportiveness

BFI Conscientiousness

Pearson Correlation

.362**

.295**

Sig. (2-tailed)

.000

.001

N

119

119

BFI Extroversion

Pearson Correlation

.113

.120

Sig. (2-tailed)

.220

.195

N

119

119

BFI Agreeableness

Pearson Correlation

.321**

.264**

Sig. (2-tailed)

.000

.004

N

119

119

BFI Neuroticism

Pearson Correlation

-.290**

-.283**

Sig. (2-tailed)

.001

.002

N

119

119

BFI Openness

Pearson Correlation

.321**

.263**

Sig. (2-tailed)

.000

.004

N

119

119

** Correlation is significant at the 0.01 level (2-tailed)

This finding was both interesting and confusing and further investigation was undertaken to determine any possible reasons for the statistically significant correlations for one school but not for the other. No obvious reason exists to explain why such a pattern would present itself. The first investigative analysis was to plot the scatterplots of the correlations. The scatterplots for instructor engagement and the personality factor of conscientiousness for both schools are presented in Figure 1.

Figure 1: Scatterplots for Instructor Engagement and Conscientiousness Personality Factor
image

An examination of these two scatterplots clearly shows an outlier in the data for the School of CJ. What is interesting is that it is a consistent outlier for both the BFI Conscientiousness factor and student evaluations of instructor engagement. In Figure 2 we can see the scatterplots for the personality factor of openness and overall supportiveness.

Figure 2: Scatterplots for Overall Supportiveness and Openness Personality Factor
image

Once again there is an outlier in the data for the School of CJ. Also, the same consistency is evidenced. This instructor was very low on the BFI Openness factor and was rated low by students as being supportive of their success. To further investigate the outlier Box Plots were created for each school and for the two student evaluation statements and the BFI factors of conscientiousness and openness. These plots are presented in Figures 3 and 4.

Figure 3: Box Plots for BFI Factors of Conscientiousness and Openness
image
An inspection of these Box Plots for BFI factors shows that the outlier is the same respondent (#47), who is significantly lower on the BFI factors of conscientiousness and openness. In Figure 4 the Box Plots for the two student evaluation statements are presented.

Figure 4: Box Plots for Student Evaluations of Instructor Engagement and Overall Supportiveness
image

An inspection of the Box Plots for the student evaluations shows the outlier is significantly lower on both evaluative statements. The interesting finding from these plots is that once again the same instructor is the outlier in all four plots, ID # 47. The question was whether to delete this outlier and re-run the correlational analysis or to keep this instructor in the data set. The first impulse was to delete the outlier and this would yield no statistically significant correlations for the entire sample or for either school. While this might be a valid finding, the other concern is arbitrarily deleting what appears to be valid data for one instructor. It might be possible that the instructor did not complete the BFI survey in the same way that the others did but again there is no evidence that this was the case. The student evaluations of this instructor were low compared to all other instructors in the sample. The fact that the BFI factors were lower than the scores for all other instructors and that the students rated this instructor low on the student evaluations tends to support the contention that the data for this instructor is valid and should not be arbitrarily deleted from the analysis.

An examination of the scatter plots and the box plots clearly show that both schools have very similar patterns, except for the outlier instructor. The scatter plots show that both BFI factors and both student evaluation statements are truncated at the lower end of the scale. The inclusion of the outlier for the school of CJ did result in the statistically significant correlations between the four BFI factors and the two student evaluation statements. The possible implications of this are discussed in that section of this paper.

From Table 2 using Cohen's (1988) conventions it can be seen that there is a moderate effect size for BFI Conscientiousness and Engagement (.362), BFI Agreeableness and Engagement (.321), and BFI Openness and Engagement (.321). There is a close to moderate effect between BFI Neuroticism and engagement (-.290).  This would indicate that students positively evaluate faculty members who are conscientious, agreeable, and open, but not neurotic, as engaging them with course materials. The same pattern of faculty personality factors, but to a slightly lower degree, was perceived by students as supporting their success.

Using the value of .10 to be the threshold for a small effect, it can be seen there are no useful correlations between the BFI factor of Extroversion and Engagement. To determine if there might be a combination of BFI factors that could be used to predict either of these student evaluations for faculty in CJ, a stepwise multiple regression procedure was conducted for each evaluative statement. From Table 4 it can be seen that there is a statistically significant equation (R = .407, Adjusted R2 = .152) using conscientiousness and openness to predict instructor engagement. The equation to predict overall supportiveness (Table 5) only included conscientiousness and the adjusted R2 is only .079. Consequently, the only significant finding related to BFI factors and student evaluations is between conscientiousness and openness to predict instructor engagement.

Table 4: Stepwise Multiple Regression for Instructor Engagement


Dept

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

CJ

1

.362a

.131

.124

.295329

2

.407b

.166

.152

.290593

a. Predictors: (Constant), BFI Conscientiousness
b. Predictors: (Constant), BFI Conscientiousness, BFI Openness

Coefficientsa

Dept

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

CJ

1

(Constant)

3.704

.227

 

16.312

.000

BFI Conscientiousness

.209

.050

.362

4.202

.000

2

(Constant)

3.468

.248

 

13.993

.000

BFI Conscientiousness

.159

.054

.276

2.956

.004

BFI Openness

.115

.052

.206

2.201

.030

a. Dependent Variable: Instructor Engagement

Table 5: Stepwise Multiple Regression for Overall Supportiveness

Dept

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

CJ

1

.295a

.087

.079

.277413

a. Predictors: (Constant), BFI Conscientiousness

Coefficientsa

Dept

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

CJ

1

(Constant)

3.953

.213

 

18.535

.000

BFI Conscientiousness

.156

.047

.295

3.336

.001

a. Dependent Variable: Overall supportiveness

Results Summary
H1 There is a positive relationship between extraversion and job performance of online instructors. This hypothesis was not supported for the full sample and for each school.
H2 There is a positive relationship between agreeableness and job performance of online instructors. This hypothesis was supported for the School of Criminal Justice but not for the School of Technology.
H3 There is a positive relationship between conscientiousness and job performance of online instructors. This hypothesis was supported for the School of Criminal Justice but not for the School of Technology.
H4 There is a negative relationship between neuroticism and job performance of online instructors. This hypothesis was supported for the School of Criminal Justice but not for the School of Technology.
H5 There is a positive relationship between openness to experience and job performance of online instructors. This hypothesis was supported for the School of Criminal Justice but not for the School of Technology.

Implications

Student evaluations of instructors continue to be relied on as a major component of faculty performance in most post-secondary institutions of higher education. Most instructors are hired to teach for online institutions without meeting the hiring manager or department chair face-to-face. The hiring decision is usually based on a combination of the following: education level, prior teaching experience, specific credentials or licenses, recent publications, and tone of conversation during a series of phone interviews. Should hiring managers seek instructor applicants who indicate high levels of conscientiousness and openness to improve the possibilities of instructor engagement? Self-assessment of personality characteristics using the BFI instrument could inform and strengthen hiring decisions of academic hiring managers. If instructors know their BFI status, would it help them to understand how they approach problems and issues and how they may be perceived by others? If managers know the BFI status of their direct reports, it could help in coaching employees regarding how they may be perceived by students in an online environment.

The absence of any statistically significant correlations between the BFI factors and student evaluations for faculty members in the School of Technology and the presence of statistically significant correlations for the School of Criminal Justice when the outlier is included suggests there may be an issue with restriction in range for all variables. An inspection of the scatter plots presented in Figures 1 & 2 shows a very homogeneous pattern for both schools and the two BFI factors and the two student evaluation statements. When the outlier is removed from the School of Criminal Justice the patterns from both schools are very similar and there are no statistically significant correlations for either school. In this online university the majority of instructors are adjunct instructors. Following application screening and training all new adjuncts are monitored closely to assure compliance with university policies, procedures, and expectations. The end-of-term student satisfaction surveys for all instructors are reviewed as one part of the ongoing evaluation process. If an instructor is not meeting expectations, the chair and instructor develop a performance improvement plan that includes coaching and/or mentoring for improvement.

The result of the instructor monitoring, coaching, and mentoring process of the university is that all instructors who are retained long term usually have student evaluation scores at or above 4.0 on the 1 to 5 scale. From an inspection of Figures 1 & 2 we can see there are very few instructors below the 4.0 threshold and none, except ID #47, are below 3.5 on either of the two evaluation statements.

The presence of the outlier in the School of Criminal Justice might indicate a struggling instructor who, if performance does not improve with coaching and mentoring, will no longer be teaching classes. However, the fact that this instructor scored low on the BFI factors of conscientiousness and openness and was also evaluated very low by students may really indicate the possible relationship that would exist in the full population. It is speculation regarding the possible correlation but the restriction in range is clear on both the BFI factors and the student evaluations.

Limitations

This study was limited by using instructors, except for one, who had apparently survived any initial issues with performance and were performing well according to student evaluations. These same instructors held similar and high scores on the BFI factors. This resulted in a restriction in range for both predictor and criterion variables.

Conclusion

Teaching and learning online is here to stay. Effective online instructors may require a different skillset than required for traditional ground campus instructors. This study found instructor-self assessment of personality using the BFI was related to student evaluations of instructors in the School of Criminal Justice, when the single outlier instructor was included. Additional research is needed to examine the relationship between BFI factors and student evaluations of instructors when there is not a restriction in range in both variables. Also, additional research should include other disciplines. This study offers some evidence that there is a relationship between online instructor personality characteristics and student evaluations of their online instructors.


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Online Journal of Distance Learning Administration, Volume XVI, Number II, Summer 2013
University of West Georgia, Distance Education Center
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