The research argued that emotional presence should exist as a critical presence in the Community of Inquiry (CoI) framework. The current study focused on non-traditional graduate students in higher education. Both qualitative and quantitative data showed that emotion evidently emerged as a natural component in CoI among non-traditional students.
The Community of Inquiry (CoI) framework posits that cognitive presence, social presence, and teaching presence are three components of structuring the collaborative teaching and learning process in an online learning environment (Garrison, Anderson, & Archer, 2000). Meanwhile emotion has long been researched in educational settings (Pekrun, 2006; Phelps, 2006; Tyng, Amin, Saad, & Malik, 2017) and considered as an important factor in successful online learning (Artino, 2012; Gilmore & Warren, 2007; Marchand & Gutierrez, 2012; Swerdloff, 2015). Lipman (2003) argued that online learning was a process where “emotive experience, mental acts, thinking skills, and informal fallacies” (p. 18) work together to improve reasoning and judgment. “Emotional expression” appears as one of the three categories under the social presence in the CoI framework. Cleveland-Innes and Campbell (2012) further added emotional presence to CoI and defined it as “the outward expression of emotion, affect, and feeling by individuals and among individuals in a community of inquiry, as they relate to and interact with the learning technology, course content, students, and the instructor” (p. 283). It has been argued that emotional presence should exist as a unique presence other than being combined into social presence. By examining students’ online learning experiences in a one-to-one online math coaching program, Stenbom, Hrastinski, and Cleveland-Innes (2016) suggested that emotional presence could be outside of social presence. Aactivity emotion (Pekrun, 2006) and directed affectiveness (Derks, Fischer, Bos, 2008) emerged in the one-on-one Relationship of Inquiry framework. Related research also found that activity emotion was the most common emotional presence element (Stenbom, Jansoon, & Hulkko, 2016) and emotional presence in teaching presence may foster social and cognitive presence in online learning (Majeski, Stover, & Valais, 2018).
Purpose of the Study and Research Questions
Despite the research discussed above, research on emotion and online learning are far from sufficient. Garrison (2011) argued that it was important to understand the educational purposes and its related contexts when applying the theoretical insights of CoI to build a collaborative-constructivist learning community of inquiry. Thus, the current study focused on non-traditional graduate students in higher education aiming at answering following research questions:
RQ1: To what extent emotion would emerge in the online learning process for the non-traditional adult learner students?
RQ2: What is the relationship between emotional presence and cognitive, social, and teaching presence? Does emotional presence have a significant correlation with gender, age, personal experience with computer technologies, self-paced online learning, and social media/communication tools usages?
RQ3: Do emotional, cognitive, social, and teaching presence have a significant predictive relationship with students’ satisfaction towards their online learning experiences?
Method
The students in the online master’s and doctoral programs in Educational Leadership and Higher Education in a Texas public university were invited to participate in the study. Due to the nature of the programs, students recruited were all working professionals thus were considered as non-traditional students. Participants’ cognitive, teaching, and social presence were evaluated by the 34-item Community of Inquiry survey (Arbaugh et al.’s, 2008) with ratings from 0 (strongly disagree) to 5 (strongly agree). The emotional presence was measured by Cleveland-Innes and Campbell’s (2012) six emotional presence items on the same ratings. Artino’s (2008) online course satisfaction survey was used to measure students’ online learning satisfaction. An open-ended question was used to gather students’ perceptions about their online learning experiences. Participants’ gender, age, and personal experience were also collected.
Data Analysis
To answer RQ1, a content analysis (Gbrich, 2007; Nagai, 2015; Stone, 2001) was used to identify emotion surfaced in participants’ qualitative responses, in a two-stage coding procedure that includes 15 emotional constructs (Cleveland-Innes & Campbell, 2012) and emotion categories (i.e., activity emotion, outcome emotions, and directed affectiveness) (Derks, Fischer, & Bos, 2008). To answer RQ2, descriptive statistics, correlation, and repeated measure ANOVA were used. To answer RQ3, a hierarchical regression analysis was used with emotional presence in block 1 and all other presences in block 2.
Results
Forty-seven students participated in this study, with one participant completed CoI survey only and one wrongfully filled out all ratings thus they were excluded from the analysis. The remaining 45 participants had an average age of 46.20 (SD = 11.98; range = 24 -75).
RQ1: The content analysis revealed dichotomous emotions from participants’ responses about their online learning experiences. First, out of the 15 emotional constructs (Cleveland-Innes & Campbell, 2012), “enjoyment” was identified 21 times out of 45 responses and “happiness” emerged 12 times and “pride” 5 times; whereas “frustration” 7 times, “disappointment” 7 times, and “desire” 6 times,. Other emotions found were “yearning” (2 times), “wonder” (2 times), and “unhappiness” (2 times). The second-stage analysis revealed that emerged emotions belonged to different categories: 30 showed directed affectiveness, 22 responses showed activity emotion, and 8 showed outcome emotion.
RQ2: On the quantitative survey data, the reliability of the emotional presence items was first assessed using Cronbach’s (1951) alpha. The six emotional presence items were found to be highly reliable (α = .876), which is consistent with Stenborm, Hrastinski, and Cleveland-Innes’ (2016) Cronbach’s alpha reporting (α = .74) with a similar sample size (n = 41).
A repeated measure analysis of variance, with Greenhouse-Geisser correction, revealed a significant difference among four presences, F(2.386, 107.38) = 49.514, p = .000. partial ŋ2 = .524. Emotional presence held significant differences with cognitive presence, t(45) = 9.627, p = .000, social presence, t(45) = 7.136, p = .000, and teaching presence, t(45) = 8.916, p = .000. There was also a significant difference between social and cognitive presence, t(45) = 3.646, p = .001. Item level analysis on the six emotion measures was also examined. A repeated measure ANOVA, with Greenhouse-Geisser correction, revealed a significant difference among six emotional items, F(3.746, 117.493) = 8.62, p = .000. partial ŋ2 = .161. Further analysis revealed no gender difference on the emotional presence, t(43) = 1.546, p = .129. No correlation was found between emotional presence and age, r(45) = .165, p = .278k. Furthermore, no significant relationship was found between emotional presence with participants’ experiences using online computer technologies, r(45) = -.132, p = .388, and experiences with social media and communication tools, r(45) = -.042, p = .783, and experiences with self-paced online learning, r(45) = -.035, p = .821.
To answer RQ3, a hierarchical multiple regression analysis (see Table 4) showed that emotional presence alone significantly predicted online learning satisfaction, F(1, 44) = 4.847, p = .033, adjusted R2 = .079. The addition of cognitive, social, and teaching presence showed a significant improvement to the prediction, R2 change = .186, F(3, 41) = 3.553, p = .022. The entire group of independent variables significantly predicted online learning satisfaction, F(4, 41) = 4.088, p = .007, adjusted R2 = .215.
Conclusion and Discussion
Past research suggested that in structuring a collaborative teaching and learning space online, emotion should be “at least as a ubiquitous, influential part of learning” (Cleveland-Innes & Campbell, 2012, p. 285). In this study, emotion evidently emerged as a natural component under the CoI Framework among the non-traditional students with an average age of 47. The quantitative survey data revealed that emotional presence was distinct from all other components of CoI, interestingly, with a lower rating and a larger dispersion compared to other presences, which is consistent with past research. Such a discrepancy was echoed by the dichotomous emotions participants demonstrated in reflecting their online learning experiences, i.e., enjoyment/happiness vs. unhappiness/frustration/disappointment. On one side, enjoyment/happiness was repetitively spotted when participants talked about how they benefited from online learning, such as “online learning allowed me to take classes around my fulltime job as an administrator”. On the flip side, unhappiness was evident when they complained: “there is a disconnect between coursework and the dissertation process”. It is worth noting that such mixed emotions were evident among participants’ reflections.
This study demonstrated participants’ directed affectiveness, the recognition of emotions in building a relationship with professors or peers. Such emotions highlight that relationship is the key factor in building an effective online learning community. This result echoes the distinctive appearance of emotion in the survey data (regardless of gender, age, online experiences), as well as the relationship between emotion presence and students’ online learning satisfaction. Meanwhile, participants demonstrated more emotions tied to ongoing achievement-related activities compared to the outcome (Pekrun, 2006). Different from past research (Stenbom, Jansson, & Hulkko, 2016) where outcome emotion was “rare”, the emotion pertaining to the learning outcome was present in this study, and participants showed anxiety of failure for not being able to complete the degree in time. The reason behind this is that for the master’s and doctoral level non-traditional students with the major goal of completing the degree, learning outcome plays a major role in assessing their online learning experiences, thus, they often showed outcome-related emotions. The overall results imply that emotion plays an important role in building an online learning community, and emotion may be particularly important for non-traditional adult learners.