The Role of Positive Psychological States in Online Learning

Abstract

A majority of business schools and universities incorporate online pedagogy into curricula, yet scholars strive to understand the elements that influence student learning in these online communities. One framework that conceptualizes the elements of the online learning environment is the Community of Inquiry (CoI) framework. The CoI suggests teaching, social, and cognitive presences exist in the online learning environment; however, the framework does not fully conceptualize how individual-level motivational factors influence student learning. Using positive psychology theory, we suggest the CoI framework include psychological capital (PsyCap) to capture positive student-level motivational states. Our analysis of students in online business courses finds that PsyCap is a distinct online presence. Specifically, we find that teaching presence significantly relates to PsyCap and that PsyCap significantly relates to both social and cognitive presences within the CoI. We offer implications for researchers and instructors interested in enhancing student-level PsyCap and learning outcomes in the online learning environment.

Keywords

Community of Inquiry psychological capital online learning business education

Introduction

The number of online courses offered has dramatically increased in recent years with more than half of all Association to Advance Collegiate Schools of Business (AACSB) accredited institutions offering some form of online or distance education (Popovich & Neel, 2005). As online course offerings increase, scholarship related to online pedagogy is rapidly developing, yet researchers are limited in fully understanding what drives learning in the online environment. On one hand, researchers suggest students in online courses value instructor interaction, while others suggest learning is most effective in online environments when peer collaboration occurs (see Arbaugh, 2013). The Community of Inquiry (CoI) framework (Garrison, Anderson, & Archer, 2000) unites both perspectives and offers a theoretical conceptualization of how teaching presences and social presences in the online environment influence student learning, but is there another (seemingly unacknowledged) component that drives student learning in the online context?

The CoI framework, as proposed by Garrison et al. (2000), has roots in Dewey’s (1933) perspective that education is a collaborative reconstruction of experience. Garrison et al. (2000) identify cognitive and social elements that exist within an educational experience and suggest that a teaching element is also necessary to “design and integrate the cognitive and social elements for education purposes” (p. 92). The CoI framework results in the collection of teaching, social, and cognitive elements—labeled as presences—and is collectively referred to as the CoI (Garrison et al., 2000).

Teaching presence acknowledges the role of the instructor in designing and facilitating the educational experience in the online environment, whereas social presence consists of the emotional expression, open communication, and group cohesion experienced by the student (Garrison et al., 2000). Cognitive presence is noted as the “vital element in critical thinking . . . that is frequently presented as the ostensible goal of all higher education” (Garrison et al., 2000, p. 89). From a constructivist perspective, these presences represent the primary elements needed to create a learning environment with the teaching and social presences having an influence on the learning outcomes associated with cognitive presence. Research related to these relationships suggests that instructors (teaching presence) influence collaboration and learning (social and cognitive presences, respectively) and that peer collaboration (social presence) influences student learning (cognitive presence; Garrison, Cleveland-Innes, & Fung, 2010).

Most contemporary uses of the CoI framework focus on these three main presences. According to research at the intersection of motivation and instructional theory, however, certain individual-level conditions must be present for learning to occur (Hill, Song, & West, 2009; Ryan & Deci, 2000). In other words, students must have the necessary confidence to learn before they are willing to engage (Schott & Driscoll, 1997). Without the proper confidence and belief system, students are likely to encounter difficulty in the learning process. Otherwise, students who believe they can perform well are likely to be more cognitively engaged and exhibit higher learning outcomes (Bandura, 1997; Deci, Vallerand, Pelletier, & Ryan, 1991; Eccles, Wigfield, & Schiefele, 1998; Pintrich & Schunk, 2002).

Despite a long interest in learning communities (e.g., Shrivastava, 1999), the acknowledgement of individual factors within the online learning environment is nascent (e.g., Shea & Bidjerano, 2010) and our understanding of how individual-level motivational factors influence the presences within the CoI remains to be fully articulated. Currently, the CoI framework considers teaching, social, and cognitive presences within the online context but lacks a developed conceptualization of intrinsic, student-level, self-regulated factors that influence learning. Such factors are important to understand because, ultimately, students must take initiative to successfully navigate an online learning environment, and in this context, students are less motivated by external factors such as the instructor (as is more common in face-to-face learning environments). Individual motivation, then, plays a key role in success within an online learning environment, yet remains an area relatively understudied (Shea & Bidjerano, 2010). Therefore, in this study, we propose that individual-level motivational factors are a useful element to expand the CoI framework and more fully conceptualize the scope of presences that exist within the online environment. To do so, we rely on psychological capital (PsyCap), a construct from positive psychology, to elucidate the broader components underlying individual-level success in the online learning environment.

With a focus on the positive aspects of individual success, PsyCap is an individual-level state consisting of self-efficacy, hope, optimism, and resilience (Luthans, Luthans, & Luthans, 2004). The current CoI literature acknowledges the existence of teaching, social, and cognitive presences within a community of learning; however, we suggest that an additional element, acknowledging an individual’s motivation to learn, is also appropriate when understanding the factors that influence student learning. In other words, we suggest that PsyCap is useful to reveal the individual-level psychological factors associated with learning. Therefore, the primary objectives of this investigation are to (a) propose PsyCap as a type of presence within the CoI framework and (b) empirically examine the relationships among PsyCap and the three existing presences of the CoI framework.

Using a sample of 275 students from five online undergraduate management courses, we investigate whether the instructor’s role in the online environment (teaching presence) relates to PsyCap. Furthermore, we test whether PsyCap positively influences the student’s social presence and cognitive presence in the online learning environment. We find that teaching presence positively relates to PsyCap and that PsyCap positively relates to both social presence and cognitive presence. Overall, the findings suggest that PsyCap is an appropriate extension of the CoI and has significant relationships with the teaching, social, and cognitive presences.

This study contributes to the state of current research on these topics in numerous ways. First, we suggest that expanding on the acknowledged presences within the CoI will more fully account for the scope of presences within the online environment that affect student learning. Second, this examination sheds light onto how learners are motivated within a CoI, thus giving instructors practical insight into methods that strategically encourage self-efficacy, hope, optimism, and resilience in the online environment. Third, by utilizing theory from positive psychology, this research departs from traditional psychology research, which often examines “what goes wrong with individuals” (Gable & Haidt, 2005, p. 104) and focuses on positive psychological traits in an online environment. Instructors and researchers are able to have a more detailed understanding of the positive aspect of student-centered motivational factors that drive learning outcomes. Few studies integrate positive psychology theory into management education scholarship, and by doing so, we seek to better understand how acknowledging such factors affects educational outcomes.

Theoretical Background and Hypotheses

Community of Inquiry (CoI)

As institutions are turning toward online course delivery systems, faculty and students are developing new skills to embrace course delivery from the traditional one-way asynchronous design to a two-way dialogic, interactive experience (Daspit & D’Souza, 2012; Shea & Bidjerano, 2009). Numerous factors exist in an online educational context and the CoI is a theoretical framework that allows for a conceptualization of presences within the learning environment (Garrison et al., 2000). The CoI framework highlights three factors that exist within an online learning environment: teaching presence, social presence, and cognitive presence.

Teaching presence has two main functions that include course design and instructor-led facilitation. Instructors are responsible for designing courses that foster cognitive and social presences (Garrison et al., 2000). With the advent and use of increasingly synchronous technology, the course instructor is only one party who can create a sense of connectedness within the online CoI (Shea et al., 2012).

Students also assume a critical role in creating a fruitful online learning environment. Social presence involves students’ abilities to project “personal characteristics” into the online environment and encapsulates the interpersonal interactions that occur via the online platform (Garrison et al., 2000, p. 89). The third element, cognitive presence, is understood as an individual’s ability to “construct meaning through sustained communication” within the community (Garrison et al., 2000, p. 89). Cognitive presence manifests via various stages of learning including triggering events (initiation of the learning action), exploration (information search), integration (synthesizing knowledge into a coherent idea), and resolution (problem solving; Garrison et al., 2000; Shea et al., 2012). When acknowledged collectively, it is the synergy among the teaching, social, and cognitive presences that fosters a social constructivist form of online learning and creates an online CoI (Garrison et al., 2000; Shea et al., 2012). While the three presences are necessary elements for creating a community of learning, the CoI framework, however, does not include individual-level drivers of learning. Therefore, to highlight the role of individual motivational drivers, we examine the influence of PsyCap within the online learning context.

Psychological Capital (PsyCap)

The research of PsyCap, with origins in positive psychology and social learning theory, typically takes place within the context of a firm where recognition for understanding positive forms of individual motivation in organizational behavior and human resource management are possible (Luthans et al., 2004; Luthans, Luthans, & Jensen, 2012; Stajkovic & Luthans, 1998). PsyCap focuses on an individual’s strengths rather than weaknesses and is measured using the dimensions of self-efficacy, hope, optimism, and resilience (Luthans et al., 2004). All four characteristics are states rather than traits, in that the states are malleable with training (Youssef & Luthans, 2007), whereas traits, such as personality, are more static.

Self-efficacy refers to a person’s conviction or confidence in his or her skills to solve a task or problem within a given context (Stajkovic & Luthans, 1998) and stems from a person’s ability to self-reflect. Stajkovic and Luthans (1998) distinguish between self-esteem and self-efficacy, as the former focuses on a person’s universal abilities while the latter is task specific. Hope is “the sum of perceived capabilities to produce routes to desired goals, along with the perceived motivation to use those routes” (Snyder, 2000, p. 8). By basing their conceptualization on this definition, Luthans et al. (2004) noted that hope involves the interaction of successful agency (goal orientation) and pathways toward meeting stated goals. Agency includes the willpower to achieve a goal, while pathways involve an individual’s ability to cope with obstacles that may thwart goal achievement (Luthans & Jensen, 2002; Snyder, 2000).

Optimism embodies a person’s ability to understand events based on permanence and pervasiveness (Luthans et al., 2004). Permanence deals with time, while pervasiveness concerns space. Put differently, an optimist views challenges as external to the self, temporary, and specific to the situation rather than a reflection of an overall ability (Youssef & Luthans, 2007). Finally, resilience reflects a person’s ability to “‘bounce back’ from adversity or even dramatic positive changes” (Luthans et al., 2004, p. 47). Resilience, especially in the face of a substantial life event, varies based on the individual and represents an ability to maintain equilibrium (Bonanno, 2004). To that end, resilience encompasses both proactive and reactive emotional states and, potentially, growth.

As noted earlier, PsyCap is important to integrate into studies of online learning environments because it allows us to dig deeper into what individual-level factors lead to success within a CoI. Simply put, self-efficacy, hope, optimism, and resilience are constructs that both the individual and instructor can alter, as they are malleable states rather than static traits. The student can project certain qualities, while the instructor can use tailored motivational activities to encourage student engagement within an online learning space. PsyCap, similar to the CoI’s cognitive presence, acknowledges the presence of the individual student; however, while the cognitive presence is specific to individual learning outcomes, PsyCap represents individual-level motivations that drive the development of learning outcomes.

Identifying PsyCap as a component of the larger CoI framework aligns with better understanding the role of metacognition in online learning (Garrison & Akyol, 2012). With the addition of metacognition—an individual-level construct dependent on cognitively and motivationally engaged learners (Garrison & Akyol, 2012)—scholars are beginning to appreciate the role of student learners within the CoI (Shea & Bidjerano, 2010). Learners rely on individual-level motivators when deciding to actively engage in a learning community, and by properly fostering those motivators, the presence of desired outcomes is more likely.

PsyCap and the CoI

The CoI accounts for instructor influences (teaching presence), group dynamics (social influence), and student cognition (cognitive presence), yet no individual-level self-regulation is fully acknowledged within the framework. As such, there is an inherent limitation of the CoI framework in that individual-level capabilities are not expressly observed. Considering that online learning is highly participatory and relies heavily on student engagement (Shea & Bidjerano, 2010), we believe that by exploring the explicit role of individual motivation states in an online learning environment, we can expand the CoI framework. Therefore, we propose that PsyCap is a means to offer insight into factors that drive student learning in an online environment and support the creation of a successful online learning community. Sharing and collaboration are important attributes in developing metacognitive aspects of online learning, and ultimately it is up to the individual how he or she desires to participate and learn in the online community. PsyCap acknowledges the individual psychological elements essential to fostering a CoI, making it a fitting individual-level presence that manifests in the online learning environment.

PsyCap and Teaching Presence

PsyCap is theoretically grounded in the idea that positive perceptions allow individuals to achieve success (Harms & Luthans, 2012). A positive psychological perspective is related to an individual-level state given that the perspective is malleable and open to development (Brandt, Gomes, & Boyanova, 2011; Luthans et al., 2004). Given the state-like nature of PsyCap, researchers suggest that human resource development strategies can be used to develop PsyCap by laying out a clear plan of action (to build self-efficacy; Bandura, 1997; Luthans et al., 2004), developing clear personal and organizational goals (to build hope; Luthans et al., 2004), replacing dysfunctional with more constructive beliefs (to build optimism; Luthans et al., 2004), and creating strong employer–employee psychological contracts (to build resilience; Luthans, Vogelgesang, & Lester, 2006).

In the CoI, the teaching presence conceptualizes the influence of the instructor within the learning environment through course design and facilitation. Teaching presence is the central, organizing element of the CoI (Arbaugh, 2013) given its significant influence on student satisfaction, sense of community, and perceived learning (Garrison & Arbaugh, 2007). Previous evidence shows teaching presence has a direct influence on the social and cognitive presences within the CoI (e.g., Garrison et al., 2010; Shea & Bidjerano, 2009), which supports the central influence of the teaching presence.

In an online learning environment, the manner in which the instructor facilitates discourse by providing individual feedback and engaging course participants is likely to support the creation of a psychological contract between the student and instructor. Similarly, creating clear goals and providing instruction (through the use of well-designed syllabi and similar tools) are means the instructor uses to influence the development of self-efficacy and hope to foster a CoI. Furthermore, through individual- and group-level feedback, the instructor has the opportunity to cultivate student beliefs thereby enhancing optimism and resilience. Given the guidance-related factors of teaching presence, the instructor in an online learning environment is likely to influence the PsyCap of the student.

Hypothesis 1: Teaching presence positively relates to PsyCap.

PsyCap and Social Presence

PsyCap is shown to directly influence in-role behaviors, organizational citizenship behavior directed toward individuals (OCBI), and organizational citizenship behaviors directed toward the organization (OCBO; Gooty, Gavin, Johnson, Frazier, & Snow, 2009). Individuals engage in OCBIs when performing extra-role behaviors for individuals by listening to, taking a personal interest in, and sharing knowledge with others (Williams & Anderson, 1991). Given that PsyCap shows positive influence on OCBIs in organizations, we suggest that a similar relationship holds true for students in online learning environments.

The social presence in the CoI consists of the ability to openly communicate and develop a sense of cohesiveness within the learning environment (Arbaugh & Benbunan-Fich, 2006; Garrison & Arbaugh, 2007). We suggest that the student’s PsyCap in the online learning environment manifests similarly to the employee’s PsyCap in organizations (Jafri, 2013). Specifically, the student with a higher level of PsyCap is more likely to listen to contributions of, take a personal interest in, and share knowledge with others. Shared interests within the CoI are likely to yield increased interest in the community and concern for success, similar to an organizational context (Larson & Luthans, 2006). Such a relationship leads to increased organizational commitment, performance, and satisfaction among individuals (Luthans, Youssef, & Avolio, 2007). Therefore, the student with a high level of self-efficacy, hope, optimism, and resilience is more likely to experience a higher level of social presence in an online learning environment.

Hypothesis 2: PsyCap positively relates to social presence.

PsyCap and Cognitive Presence

Numerous studies substantiate the influence of PsyCap on workplace performance (Gooty et al., 2009; Luthans, Avolio, Avey, & Norman, 2007; Luthans, Avolio, Walumbwa, & Li, 2005; Luthans, Avey, Avolio, & Peterson, 2010; Stajkovic & Luthans, 1998; Youssef & Luthans, 2007), creativity (Sweetman, Luthans, Avey, & Luthans, 2011), personality across culture (Brandt et al., 2011), and employee well-being (Culbertson, Fullagar, & Mills, 2010). Furthermore, a recent meta-analysis suggests PsyCap positively influences job satisfaction, organizational commitment, psychological well-being, citizenship, and multiple measures (self, supervisor, and objective) of performance (Avey, Reichard, Luthans, & Mhatre, 2011). Given that performance in an organizational environment and performance in academic settings are related given an individual’s general cognitive ability (Kuncel, Hezlett, & Ones, 2004), it is likely that PsyCap within the workplace will also manifest similarly in a learning environment.

As suggested in instructional and motivational theory, the student exhibits higher learning outcomes when actively engaged with course material. “Students are not mere sponges who absorb information provided by a teacher and countless articles and books; they are social creatures who learn through interaction, open discourse, application, and experience” (Bryer & Seigler, 2012, p. 429). Therefore, it becomes important to empower the student to engage in a social learning environment, and we argue that PsyCap offers a means through which the learning environment, and ultimately student learning, is enhanced. Thus, we suggest that the student with a higher level of PsyCap is better equipped to handle the rigors of online curricula, given their higher levels of self-efficacy, hope, optimism, and resilience, and more likely to experience enhanced learning.

Hypothesis 3: PsyCap positively relates to cognitive presence.

Method

Sample

Participants in this study included students enrolled in an AACSB-accredited college of business at a large university in the southwestern region of the United States. Sampling comprised five class sections across three undergraduate business courses. These courses included the subjects on human resource management, organizational behavior, and introduction to management. Each course section was administered fully online and data were collected via online questionnaires.

Students received extra credit for completing the questionnaire, and of the 303 students enrolled in the five sections, 275 responses were received and deemed usable (91% usable response rate). Participants averaged 26.9 years of age (ranging from 18 to 63) with 43.3% being male, 56% being female, and 0.7% electing to not disclose gender. The ethnic distribution of the sample was 56% White/Caucasian, 17% Hispanic/Latino, 14% Black or African American, and 5% Asian/Pacific Islander. The preponderance of students was seniors and had taken between three and four online courses previously. Gathering responses toward the end of the academic term allowed appropriate time for the emergence of the specified phenomena of interest in the study.

Measures

PsyCap

Items for all measures were assessed using a 5-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree). Twenty-one items from the PsyCap questionnaire were used to measure PsyCap (α = .89). The PsyCap construct is composed of four dimensions (self-efficacy, hope, optimism, and resilience) and was adapted from Luthans et al. (2007).

Teaching Presence

Teaching presence (α = .95) consists of two dimensions: facilitating discourse and direct instruction (Shea, Li, & Pickett, 2006). The dimension of facilitating discourse relates to the instructor’s role in supporting knowledge exchange and the dimension of direct instruction acknowledges the role of the instructor in the instructional design of the course. A total of 13 items assessed both dimensions. All items measuring teaching, social, and cognitive presences were adapted from Arbaugh et al. (2008).

Social Presence

Social presence (α = .88) consists of three dimensions: emotional expression, open communication, and cohesion (Rourke, Anderson, Archer, & Garrison, 1999). Emotional expression accounts for the ability of the individual to express himself or herself in the online environment, which is a defining element of social presence (Garrison et al., 2000). The dimension of open communication recognizes knowledge exchange within the community, and cohesion is a reflection of the “togetherness” of the students in the learning environment. A total of eight items assessed social presence.

Cognitive Presence

Cognitive presence (α = .94) contains four stages of learning: triggering event, exploration, integration, and resolution (Garrison, Anderson, & Archer, 2001). The 12 items used in the study were in alignment with the four dimensions of Dewey’s (1933) model of learning. Dewey’s model suggested that the problem is first identified (triggering event), alternatives explored, meaningful ideas constructed (integration), and the problem resolved.

Controls

Similar to previous studies by Arbaugh (2007) and Garrison et al. (2010), we instituted controls for participant age, participant gender, number of previous online courses taken by the participant, and the subject matter of the course. These controls were useful when examining the variance in respondents’ perceptions for each construct.

Common Method Bias

Prior to administering the survey, the researchers implemented procedural controls to reduce the common method bias inherent in the research design (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Statistical evaluations of common method bias occurred following data collection. First, we conducted a Harman single-factor test using an unrotated principle component factor analysis with varimax rotation. The results of the test indicated sufficient variability with a single factor accounting for only 32.82% of the variance. Next, using structural modeling techniques, all items were loaded onto a single latent factor and the single factor model resulted in poor overall fit (χ² [539, n = 275] = 6725.02; p < 0.001; comparative fit index [CFI] = 0.52; root mean square error of approximation [RMSEA] = 0.11; Standardized root mean square residual [SRMR] = 0.11). The results from these tests suggest that common method variance was unlikely to confound the interpretations of results.

Results

Measurement Model

Given the primary objective of the study to expand the CoI framework to include the influence of individual motivational states explained by PsyCap, structural equation modeling was chosen to analyze the data given its ability to examine multiple relationships simultaneously (Hair, Black, Babin, Anderson, & Tatham, 2006). We conducted all analyses with SPSS version 22 and AMOS version 22. For structural analyses, AMOS software is comparable to other structural equation modeling software (Hox, 1995) indicating minimal differences among software platforms. A test of Hoelter’s Critical N (CN; Garson, 2012) determined sample size appropriateness. A review of all CN’s for the first- and second-order confirmatory models revealed CN < 200 at both the p < .01 and p < .05 levels, respectively, as recommended by Bagozzi and Yi (1988). This result indicates the sample size used in this study was adequate for structural modeling analyses.

To assess the factor structure of the data, we conducted a confirmatory factor analysis on the latent constructs. First, an examination of PsyCap latent construct took place. As recommended by Hair et al. (2006) and Byrne (2010), all factors were examined to ensure a significant (p < .05) factor loading of 0.50 or greater on the intended dimension. A review of the modification indices took place for each factor. An examination of factor loadings suggested that three items needed to be removed from the latent PsyCap construct with all other items loading properly on the respective dimensions (χ² [183, n = 275] = 386.64, p < .001; CFI = 0.93; RMSEA = 0.06; SRMR = 0.06).

Second, we examined the teaching, social, and cognitive presence latent constructs simultaneously given evidence of their predetermined relationships as components of the CoI framework (e.g., Garrison et al., 2010). The significance, factor loadings, and modification indices were examined for all factors, and the results demonstrated that all items loaded on the factors in which they were intended to measure (χ² [24, n = 275] = 59.06, p < .001; CFI = 0.97; RMSEA = 0.07; SRMR = 0.03).

Third, by combining all latent constructs into a full measurement model we examined the overall fit for the hypothesized, second-order structure. By aggregating the items on to each of their intended factors, we were able to confirm the latent constructs and create our proposed four-factor measurement model consisting of PsyCap, teaching presence, social presence, and cognitive presence. Proper significance, factor loadings, and modification indices were noted and fit indices suggested the measurement model exhibited appropriate fit (χ² [59, n = 275] = 136.50, p < .001; CFI = 0.97; RMSEA = 0.07; SRMR = 0.06).

The measurement model was then further examined for convergent and discriminant validity. In addition to the confirmation of appropriate higher order factor loadings, by examining Cronbach’s (1951) alpha as a measure of internal consistency, we found support for convergent validity. All alphas were above Nunnally’s (1978) threshold of 0.70. Table 1 contains the means, standard deviations, and correlations for all constructs.

Table 1.

Construct Means, Standard Deviations, Correlations, and Reliabilities.

Construct	M	SD	1	2	3	4
1. PsyCap	3.92	0.22	(.89)
2. Teaching presence	3.99	0.19	.48	(.95)
3. Social presence	3.73	0.26	.44	.65	(.88)
4. Cognitive presence	3.81	0.40	.47	.71	.64	(.94)

Note. PsyCap = psychological capital. All correlations significant at p < .01; Cronbach’s alpha noted in parentheses on diagonal.

A comparison of the maximum shared variance and the average shared variance of the constructs versus the average variance explained provided support for discriminant validity. This conservative approach indicates that the constructs discriminate well, as all values for average variance explained were greater than maximum shared variance and average shared variance. Table 2 provides the details of this analysis. The results of these analyses indicate that PsyCap is a distinct component when analyzed among the other presences of the CoI.

Table 2.

Factor Loadings, Construct Reliability (CR), Average Variance Explained (AVE), Maximum Shared Variance (MSV), and Average Shared Variance (ASV).

	Teaching presence	Social presence	Cognitive presence	PsyCap
Facilitating discourse	0.97
Direct instruction	0.89
Emotional expression		0.79
Open communication		0.72
Group cohesion		0.90
Triggering event			0.86
Exploration			0.87
Integration			0.90
Resolution			0.89
Self-efficacy				0.49
Hope				0.74
Resiliency				0.66
Optimism				0.64
CR	0.93	0.85	0.93	0.73
AVE	0.87	0.65	0.77	0.41
MSV	0.58	0.52	0.58	0.30
ASV	0.46	0.43	0.46	0.28

Note. PsyCap = psychological capital.

Structural Model

Given appropriate fit of the second-order measurement model, we then conducted an analysis of the structural paths. Analysis of the structural model indicated acceptable fit (χ² [95, n = 275] = 194.56, p < .001; CFI = 0.96; RMSEA = 0.06; SRMR = 0.06; consistent Akaike’s information criterion [CAIC] = 578.33). Figure 1 illustrates the hypothesized model with standardized path coefficients.

Figure 1.

Role of psychological capital in the community of inquiry.

Hypothesis 1 predicts teaching presence positively relates to PsyCap. In the structural model, the relationship between teaching presence and PsyCap is significant (β = .36, p < .01). Hypothesis 2 predicts PsyCap positively relates to social presence, and the results suggest the path between PsyCap and social presence is also significant (β = .21, p < .05). Finally, Hypothesis 3 predicts PsyCap positively relates to cognitive presence, and results indicate the relationship is significant (β = .18, p < .05). Sufficient support of all hypotheses provides evidence to confirm that PsyCap has significant and positive relationships with the teaching, social, and cognitive presences within an online learning environment.¹

Post Hoc Analyses

Nomological Validity

Even though the existing relationships among the presences of the CoI framework are not hypothesized in this study due to prior empirical confirmation (Garrison et al., 2010), we separately examined the core CoI presences to confirm whether the data support the existing configuration as noted in extant theory. We find that teaching presence positively relates to cognitive presence (β = .47, p < .05), teaching presence positively relates to social presence (β = .63, p < .05), and social presence positively relates to cognitive presence (β = .30, p < .05). Therefore, we conclude that the CoI framework observed in the context of this study is in alignment with previous empirical observations and theory, thereby supporting nomological validity.

Demographic Differences

To better inform practical implications garnered from this study, we conducted additional analyses to examine whether significant differences exist for students when considering age, gender, and number of previous online courses. Specifically, we use a series of independent sample t tests to examine whether group differences manifest across students’ PsyCap, teaching presence, social presence, and cognitive presence. The single significant difference (p < .05) noted across all groups is the comparison of social presence across student age groups: nontraditional students (students whose age is greater than 23 years) reported significantly higher perceptions of social presence than traditional students (aged 18 to 23 years).

To further examine age and social presence, we test for significance with the three first-level factors of social presence (emotional expression, communication, cohesion) and age. We find a significant difference between age groups (traditional vs. nontraditional) with respect to open communication (p < .01) and cohesion (p < .05). No significant difference exists between these two age groupings for emotional expression. This finding contradicts conventional wisdom that younger students are more likely to engage in online social interaction in an open and collective manner. In fact, these results suggest that older students have a heightened perception of open communication and are more likely to feel part of the CoI. Thus, instructors are encouraged to be mindful of such differences and consider community building activities to enhance learning environment cohesiveness (consider adaptation of the activity recommended by Neilsen, Winter, & Saatcioglu, 2005).

Discussion

Online courses are rapidly becoming a prominent component of business education curriculum and researchers are striving to more fully understand how phenomena emerge and influence student learning in the online environment. The CoI framework offers a useful conceptualization of the teaching, social, and cognitive presences in the online environment, yet a dearth of studies remains detailing the role of individual-level motivators related to the CoI elements. Shea and colleagues (2010, 2012) begin to fill this gap by noting the importance of a learner-oriented presence within the CoI, and we extend the literature of online learning communities by including measures of individual-level motivational states. By finding support for adding student motivational states, we advocate for an extension of the CoI to further acknowledge the role of the individual. To this end, we investigate the relationships among PsyCap and the three presences of the CoI framework.

Our findings suggest that PsyCap has an influential role within the CoI. Specifically, we find that PsyCap and cognitive presence have a significant relationship. This result is in line with prior studies that find PsyCap predicts individual work-related performance (e.g., Luthans et al., 2007; Luthans et al., 2010; Sweetman et al., 2011) and academic performance (Luthans et al., 2012). Our findings offer additional confirmation that PsyCap has a similar, positive influence on student learning within the context of an online course. Furthermore, our findings indicate that PsyCap influences social presence in the online environment. In other words, students who are generally more positive and confident are likely to contribute in collaborative exchanges within the medium of an online course. These results extend research on the influence of PsyCap on citizenship behaviors and knowledge exchange (e.g., Gooty et al., 2009) by demonstrating that similar relationships exist within an online educational environment.

Last, we find that the presence of the instructor in the online environment (teaching presence) is significantly related to PsyCap, which builds on previous research suggesting that teaching presence influences both social and cognitive presences (Garrison et al., 2010). Our study confirms the instructor has a broad influence within the learning environment, which underscores the importance of the instructor in this context. Through instruction and course design, the instructor has a significant and direct influence on student learning (cognitive presence), discourse among students (social presence), and the extent to which students are motivated by self-efficacy, hope, optimism, and resilience. In all, the results advance the boundary of the CoI framework.

Implications for Researchers

By integrating PsyCap into the CoI framework, we expand the conceptualization to acknowledge the teaching, social, cognitive, and now positive individual motivational states exist within an online learning environment. This finding extends the work of Shea and colleagues (2010, 2012), who suggest that incorporating a learner-centered presence adds scope and accuracy to the online learning framework. Previous attempts at integration suggest such a learner-centered presence may have relationships with the teaching, social, and cognitive presences (e.g., Shea & Bidjerano, 2012; Shea et al., 2012), and our empirical analyses confirm the theoretical extension of the CoI framework to include individual motivational states.

While our integration of PsyCap offers a broadened representation of the presences in an online environment, we encourage future researchers to continue investigating other self-regulative behaviors and motivations that may similarly influence collaboration and learning. For example, intrinsic motivation is related to the natural human propensity to learn (Ryan & Deci, 2000), which raises the question of whether individuals with higher levels of intrinsic motivation are more likely to engage in collaboration and thus exhibit higher levels of learning in online environments. Is the intrinsic–extrinsic dichotomy another appropriate means for examining the learning presence with the CoI? Moreover, researchers are encouraged to examine the role of other psychological states on student success as this study focused on positive elements. How can instructors ameliorate negative states in an online environment where indicators, such as body language or tone, might not be present?

Additionally, our findings suggest that PsyCap delivers a deeper understanding of student motivational states to make clearer a larger picture of online pedagogy than using the CoI framework alone. In reviewing the literature, we note few studies that integrate PsyCap into an online learning space or a more traditional learning environment. Considering our significant findings, we encourage researchers to extend our inquiry into other disciplines, as well as in face-to-face or hybrid settings. Our sample consists of students enrolled in management classes, but perhaps the influence of PsyCap manifests differently across disciplines. Before proclaiming generalizability, investigation within other subjects needs to take place. Moreover, students in face-to-face environments provide instructors with immediate feedback responses (questions, looks of confusion, nonverbal cues) that might be missing in an online environment. In those settings, can an instructor more quickly adjust his or her style to positively influence PsyCap? If so, how? If not, why? Put simply, do our findings hold when the educational environment changes from online to face-to-face or even to hybrid classroom learning?

Last, the significant difference found between the age groupings in the post hoc analysis on the three social presence dimensions of the CoI warrants additional investigation. What are the causes for the perceptions of social cohesion and open communication being stronger among the older group of students? Why are younger students, who are part of the “technology generation” not more comfortable engaging in the online social presence? Does context matter? Such differences warrant further investigation to explain these initial insights.

Implications for Instructors

Given the support of the findings in this study, and the state-like nature of PsyCap that allows for development (Luthans et al., 2010), we offer recommendations for instructors interested in leveraging the benefits of PsyCap for online courses. Specifically, one means for developing the PsyCap of students is by offering a PsyCap training session within the online course. For example, Luthans and colleagues (2008, 2010), building on a scale developed by Luthans, Avey, Avolio, Norman, and Combs (2006), find that groups receiving the Psychological Capital Intervention training model exhibit significant changes in PsyCap compared with groups receiving a controlled training. The training includes strategies designed to develop each dimension of the individual’s PsyCap, and thus, for instructors, administration of this type of training exercise early in the course will allow students to develop self-efficacy, hope, optimism, and resilience, and thereby positively influence learning outcomes.

Similar to Luthans, Avey, and Patera (2008), PsyCap training is shown to be effective in an online environment. For their study, Luthans et al. (2008) deploy personalized training to adult professionals and experience similar outcomes in an online environment to that of a face-to-face training environment. Respondents to the online survey report higher levels of PsyCap after the training intervention (Luthans et al., 2008). The findings indicate that PsyCap can be taught in an online environment and the training is likely suitable for integration into higher education courses.

Given the influential nature of the teaching presence on PsyCap, we encourage instructors to remain conscious of how their influence affects students within the learning environment. For instructors interested in directly influencing students’ PsyCap, Luthans et al. (2012) offer development techniques including (a) setting high expectations for students progressing from simple to more complex tasks to enhance self-efficacy; (b) increasing peer tutoring or study groups to increase vicarious learning and provide students with peer role models; (c) providing sincere, developmental, and positive feedback (in the ratio of three positive comments to one negative, based on Fredrickson’s [2009] work); and (d) commenting on effort rather than intelligence.

Limitations

Although this study adds value by confirming the addition of PsyCap to the CoI and exploring its relationship with related presences, the study is not without limitations. First, PsyCap accounts for positive individual-level states and we acknowledge that a more holistic conceptualization of a learning presence should account for both positive and negative psychological states. By integrating an assessment of negative (or neutral) psychological traits (e.g., Dickerson & Kemeny, 2004), scholars may conduct a more nuanced examination of how the learning presence relates to other presences within the CoI.

Second, the PsyCap items used in this study are traditionally used in organizational settings. We employed the PsyCap measurement scale within an online educational context to examine individual motivational states and found, through confirmatory analyses, a minor number of items lacked proper specification. Elimination of poorly fit items yielded an appropriately specified measurement model, yet we encourage future researchers to further examine the applicability of the PsyCap instrument for online, educational, and other contexts.

Third, this study used a single questionnaire administered to students. The lack of multiple, lagged assessments limits the extent to which the results have a causal interpretation. Even though advanced structural modeling techniques offer rich insight into the data, we look forward to future studies that provide a causal assessment of the relationships within the CoI framework and offer further insight into the dynamic relationship among the components. Additionally, future studies are likely to confirm the extent to which mediating relationships exist within the conceptualized framework. To what extent, for example, does PsyCap mediate the relationship between teaching presence and cognitive presence? Researchers are encouraged to further examine such relationships to provide a more comprehensive understanding of how presences relate with an online educational context.

Conclusion

Even though the presence of online courses is now commonplace in most business schools, instructors continue to strive for a best practices approach targeted to enhancing student learning outcomes. The CoI offers a useful conceptualization allowing instructors and researchers to conceptualize the online learning environment and now, with a more comprehensive acknowledgment of student-level psychological states, the framework more wholly accounts for the various presences within the online learning environment. As the CoI continues to develop, it is certain to offer a useful foundation for understanding the various phenomena that contribute to student learning in an online context.

Footnotes

Acknowledgements

We are appreciative of comments received from Derrick E. D’Souza, Doug Goodman, Xueni (Judy) Dong, and David Rylander on previous versions of the article. Additionally, we are grateful to Vallari Chandna, Brooklyn M. Cole, and Victoria McKee for assistance with data collection.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

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