Chapter 2 of "Exploring the Relationship Between Social-Emotional Competencies and Student Outcomes in Online Learning Environments"
Author: Sarah K. Teeple
Chapter Two
Introduction
Online learning represents a quickly growing field within education, both internationally (Barbour et al., 2011) and domestically, with the U.S. Department of Education (2010) having estimated a 65% increase in enrollment for technology-based virtual learning by K-12 United States public school students between the years of 2002 and 2005 alone. Online K-12 programs have been around for as long as 20 years, and Gemin et al. (2017) describe the proliferation and trends in online learning over the past several decades.
The implementation of online programming in K-12 schools varies from state to state. Some states have state-led initiatives for online learning or state virtual schools, while others, like the state of Pennsylvania, do not have a state virtual school or centralized learning initiatives through the state department of education (Vadell, 2013). The inception of state virtual schools and stand-alone online schools in the late 1990s have paved the way for multiple models of virtual instructional delivery in a variety of charter, private, and traditional public schools (Gemin et al., 2017). Some students receive all of their instruction online, while others participate in online courses as a supplement to their traditional course delivery. There are three basic models for online instruction: full-time online schools, blended or hybrid schools, and traditional schools with supplemental (or web-facilitated) online offerings (Gemin et al., 2017; Picciano & Seaman, 2007). Some researchers operationalize the aforementioned models with greater specificity, by describing full-time online programs as those in which 80% or more of the instruction is provided online, blended/hybrid models as programs consisting of between 30% and 50% online instruction, and web-facilitated or supplemental programs as those in which the majority of instruction is provided face-to-face and less than 30% of instruction is provided online (Allen et al., 2016; Picciano & Seaman, 2007).
Table 2.1 Instructional Models
K-12 education is a multi-billion dollar industry in the United States alone (Gemin et al., 2017). An estimated $10.2 billion dollars is spent on hardware, $380 million on learning management systems and platforms, and $8 billion on textbooks, although the amount spent on physical books is declining as spending increases for digital content and tools. Millions of K-12 students are taking supplemental online courses, and hundreds of thousands are attending online schools full-time (Schroeder, 2019). It is unknown how many students are participating in hybrid models of instruction, but one could infer that this number is growing in conjunction with increasing enrollments of fully online and supplemental programs (Gemin et al., 2017). By 2025, it is estimated that the global online education market will balloon to over $350 billion (“$350 Billion Online Education Market”, 2019).
Online or virtual instruction as we know it today has its roots in early modes of computer-assisted instruction (CIA) that predated the world wide web and the revolution of internet-based technology (Gemin et al., 2017). The University of Illinois spearheaded the PLATO project in the 1960s involving computers as a means of instructional delivery. The PLATO system is considered an important milestone in computer-mediated communication and instruction. The project was taken over by the Control Data Corporation in the 1970s, and continued to evolve for usage in higher education, as well as in military and corporate simulation and training. PLATO Learning and NovaNet were two programs that emerged from the larger PLATO project; PLATO Learning is now Edmentum, and NovaNet was used for a time by Pearson. Earlier iterations of online programs like the CIA systems that emerged from PLATO were largely focused on credit recovery, and indeed, this remains a key component and application of online learning today (Gemin et al., 2017).
Another precursor to common forms of online education as we know them today was the use of distance learning, which was primarily aimed at providing instruction to homebound students through the use of print resources, CD-ROMS, and tele-conferencing (Gemin et al., 2017). Distance learning was later used to provide college preparatory courses or Advanced Placement opportunities for students in areas where such opportunities would not otherwise exist, such as urban and rural schools. As the technology improved and the desire for alternative instructional models increased, distance learning via online models evolved. Even before the COVID-19 pandemic, it was estimated that nearly three million K-12 students were enrolled full-time in online learning, for a myriad of reasons (Schroeder, 2019). Motivations for fully online learning include seeking personalized learning at an individual pace or alternatives to traditional instruction in struggling school districts.
Regardless of the basic instructional model and the amount of instruction received online, a variety of digital resources and tools are utilized to provide instruction. These tools can include content websites, content-area specific software applications, and classroom management software or learning management systems (LMSs). In addition, third party suppliers (or vendors) may provide online or digital learning programs that are typically monitored and coordinated by the student’s school (Gemin et al., 2017). Vendors may coordinate directly with a school or district, or they may go through intermediate suppliers such as regional consortia or service agencies, or state virtual schools. An interesting trend is that many school districts who use vendors or suppliers are not relying on one provider alone; rather, many districts are using multiple vendors to meet the needs for online instruction (Picciano & Seaman, 2007). In Pennsylvania, the roughly 500 school districts, 67 counties, and 29 intermediate units within the state have varied degrees of access to and implementation of online learning due to the state’s lack of centralized online programs or initiatives (Vadell, 2013). This also means that school districts have to grapple with the budgetary implications of their obligation to either pay for outsourced education at virtual charter schools or other external online programs compared to providing in-district virtual learning programs that are either partially or fully outsourced.
Clements et al. (2015) also summarize some key trends in online learning, although these findings are limited in geographical scope. In response to the Regional Educational Laboratory (REL) Midwest’s Virtual Education Research Alliance expressed need for more information about online schooling, Wisconsin’s and Iowa’s state education agencies surveyed public high school administrators, educators, and paraprofessionals. The survey responses illustrated some interesting trends in the use of online education in public high schools in Iowa and Wisconsin.
Credit recovery and core courses represented a large percentage of student enrollment in online courses in both states (71% and 57% of high schools surveyed, respectively, in Iowa and 66% and 73%, respectively, in Wisconsin). Insufficient teacher training was largely cited as a challenge for the Iowa schools, and course quality was a concern in both Iowa and Wisconsin. An additional concern that emerged in Wisconsin’s survey data was adequate funding to support online programming. Concerns about funding, course quality, and teacher training were echoed in the survey results of district administrators from 44 states representing 2% of school districts nationally (Picciano & Seaman, 2007). Researchers recommend that further studies evaluate student outcomes in online courses in order to better inform policy not only at the district level, but at the state legislative level as well (Clements et al., 2015).
Social Presence
Learning as a social activity is not a new concept, but Rockinson-Szapkiw et al. (2016) postulate that the growth of distance learning platforms necessitate further study into the complex relationship between perceptions of learning communities and student achievement. One such way to study perceptions of learning communities is to evaluate the notion of social presence and social community. Tu (2002, p. 34) describes online social presence as a “complicated human perception” but underscores the value in understanding social presence in order to improve instruction in online learning environments. Terry and Doolittle (2019, p. 124), meanwhile, note that “social presence has been a topic of inquiry in a number of contexts and settings with a variety of implications.” These settings extend beyond the field of education, and include applications in broader virtual communities, including social media.
Social community is a cumulative descriptor of students’ feelings or perceptions of interdependence, cohesiveness, interaction, safety, sense of belonging, and trust within the context of an educational setting (Rockinson-Szapkiw et al., 2016), whereas social presence is a related but distinct construct that describes student perceptions of feeling a sense of belonging in a learning community, as indicated by group cohesion, open communication, and affective expression (Fiock, 2020). Operationalizing social presence has been an ongoing process. Social presence theory has been hindered by a lack of specificity and consistency in the definition of social presence, as well as by a lack of valid instruments for assessing the complex variables that impact social presence (Terry & Doolittle, 2019; Tu, 2002). Some earlier tools for assessing social presence included the Social Presence and Privacy Questionnaire (SPPQ) and the Computer-Mediated Communication (CMC) attitude instrument (Terry & Doolittle, 2019; Tu, 2002).
Community of Inquiry
However, as the body of research grew and the complexity of social presence and other learning perceptions became more apparent, a new theoretical model expanded to include unique but overlapping constructs. Community of Inquiry (COI) is a framework that attempts to define the interdependency of three core factors in creating a meaningful experience for learners: social presence, cognitive presence, and teaching presence (Zidiropoulou & Mavroidis, 2019). Cognitive presence refers to student perceptions of having achieved learning outcomes through metacognitive reflection of content knowledge and skills in a given subject area, while teaching presence represents the combined effect of instructional design, the instructional delivery itself, and the facilitation of discourse or interaction on the social and cognitive aspects of learning (Fiock, 2020).
Figure 2.1 Community of Inquiry Framework
The current body of literature on social presence within a social community in online learning has largely embraced the COI model, although some researchers are beginning to investigate the possibility of adding a fourth factor (learning presence) into the existing three-factor framework (Rockinson-Szapkiw et al., 2016). Others contend that COI as a model still fails to capture the essence of social presence:
Given that its significance and utility as a psychological and pedagogical construct is being evaluated within a variety of different contexts (including Twitter, gaming, and 3D virtual world), and has begun to produce positive outcomes in educational settings, it seems that a logical next step is to conduct research that would produce a more consistent definition that can, in turn, inform appropriate instructional strategies. (Terry & Doolittle, 2019, p. 124)
Nevertheless, many current studies have employed COI in examinations of social presence, perceived learning, and learner satisfaction. Perceived learning describes a student’s perception that academic outcomes have been achieved as a result of instruction. The extent to which students feel that learning has happened can be a function of different realms or categories of student experiences. Affective learning is a category within the larger construct of perceived learning, and refers to a student’s perceptions about the teacher, the topic, and the course itself (Rockinson-Szapkiw et al., 2016).
Stenborn’s (2018) systematic analysis and review of over 100 published papers utilizing the Community of Inquiry survey between the years of 2008 and 2017 provide support for the reliability and validity of the survey tool in examining learning experiences. Therefore, although the COI model may still be evolving, it remains a valid and reliable framework for examining the complex structures that define a student’s learning experience.
Student Achievement in OLEs
The existing literature on social presence in online instruction has largely been concentrated in postsecondary institutions. Further research in K-12 settings is needed to determine if conclusions about student achievement in online settings are generalizable to students in primary, intermediate, and secondary schools (U.S. Department of Education, 2010). Many studies support the finding that students in online settings do not underperform or outperform students in traditional settings, based on the instructional environment alone. Richardson et al. (2014) cite evidence over years of empirical research that show no significant difference between traditional classroom instruction and online learning. More recently, McDaniel and Fraser (2016) sought to examine instructional technology and the effectiveness of online learning. They studied a sample of Texas middle school students, and used the The Technology-Rich Outcomes-Focused Learning Environment Inventory (TROFLEI) as a pre- and post-test. Their findings support the previous body of research indicating that there is not a significant difference in student outcomes based on an online or a face-to-face learning environment. Additional studies on perceived outcomes in online courses reveal generally positive perceptions of the efficacy of online learning (Allen et al., 2016). This provides more impetus for a focus on meaningful virtual instructional design in service of bolstering learning outcomes for students, as one can infer that outcomes are not a function of the learning environment in and of itself.
For example, Alqurashi’s (2019) research on online learning in higher education provides further support for the link between student satisfaction and self-efficacy, teacher/ student interaction, and student/content interaction. Instructors can seek to improve online self-efficacy by facilitating perceptions of performance accomplishment to build a foundation for success early in the course, as well as by providing vicarious experiences of student success, wherein students have concrete examples and are able to observe the successes of their peers, such as through exemplar work samples. In addition, teacher feedback that is timely, genuine, and constructive can help to enhance online self-efficacy. Meanwhile, the interaction of students with content can be enhanced by providing a variety of materials and opportunities for engaging with the course material.
Overall, these findings indicate that there is merit in focusing on online instructional design because effective learning environments can transcend a physical setting with appropriate planning. Conversely, a lack of training and course design could have a similarly deleterious effect on student learning if schools make a transition to online learning without proper planning and teacher training. Indeed, teacher training has emerged as a challenge in several surveys about online and blended learning (Barbour et al., 2011; Clements et al., 2015; Picciano & Seaman, 2007). Bendici (2020) emphasizes that educators must use technology to personalize learning and create engaging lessons, further underscoring the importance of teacher training.
Researching Social Presence and COI
According to the COI framework, teacher training manifests in teaching presence. Teaching presence has been found to be linked with cognitive presence, which is one construct that can support perceptions of student learning. For example, Zidiropoulou and Mavroidis (2019) set out to examine the relationship between diverse student learning styles and the three aspects of COI by using multiple tools to survey the experiences of post-graduate students who participated in distance learning courses through a Greek university. They found strong, positive correlations between social and cognitive presence, and between cognitive and teaching presence, further supporting the interconnectedness of the COI aspects. In this particular study, teaching presence was more evident, however, than social and cognitive presence. With respect to learning styles, the researchers concluded that students who lacked experience with online or distance learning appeared to prefer predetermined procedures over variety in learning modules.
Cho and Tobias (2016) cite research that failed to find a significant relationship between student interactions via online discussions, student satisfaction, and student achievement. In their experimental research study, the effects of online course discussions on student achievement and social presence were examined in a population of sophomore students for a fully online undergraduate course at a Midwestern university. While no significant differences in achievement were found between the three different groups studied, there were significant differences in the open communication and group cohesion aspects of social presence. The results help to illuminate the critical role that instructor and student interaction may have on student experiences and perceptions of being part of a learning community.
These findings support the notion that strategic design of a course is important in improving student learning experiences. Thompson et al. (2017) explored how online learning platforms can constrain versus facilitate desired behaviors and interactions. Many online courses are delivered in sequential modules via learning management systems (LMSs). A typical feature of an LMS is a discussion board for the purpose of asynchronous student discussions, which can influence the cognitive presence aspect of COI. Social presence can be more difficult to facilitate online, although synchronous chat sessions regarding course content may increase social presence and cognitive presence concurrently. Thompson et al. (2017) suggest that, to decrease the cognitive overload of a synchronous chat, students be broken up into smaller chat groups. Another tool to foster social presence is video discussion posts, although it is important to note that the data on the efficacy of such tools is still very much anecdotal. The authors recommend careful consideration of any technology tool in order to find a balance between opportunities that the tool can provide to support learning experiences while also ensuring ease of use and accessibility for students. A systematic selection process for technology tools can help educators feel assured that their use results in an enrichment of online learning.
Similarly, Fiock (2020) explains that instructors must design an online course with the multiple presences of COI in mind. For example, limited class sizes, personal pictures and profiles, welcome messages, and interactive learning activities that allow opportunity for students to share personal connections and affective experiences are elements that can facilitate social presence. Additionally, Journell (2013) suggests that teachers can facilitate social presence by setting the expectation for social interaction as a key component of the class and by providing opportunities for non-curricular social interaction and student-moderated forums. Laying the foundation for an online class as a community may also begin with student and teacher introductions, perhaps through posting videos, pictures, and/or having a face-to-face meeting at the beginning of a course when possible (Journell, 2013). Teachers can support continued interactions by creating regular opportunities for one-to-one student/teacher dialogue, video conferencing, and the establishment of regular virtual office hours (Journell, 2013). These suggestions mirror those made by Butler and Evans (2014) in support of their argument that course orientation activities and a variety of opportunities for synchronous and asynchronous interaction help to build social community and social presence.
A relationship that is less clear is the one between social presence and learning outcomes. Like Thompson et al. (2017), Lowenthal (2012) sought to examine the role of interactive discussions on student learning experiences. Lowenthal (2012) explored how social presence is evident in an online graduate class by analyzing the word counts and conducting a qualitative content analysis of course discussion board postings. The researcher also used the social presence dimension of the Community of Inquiry Questionnaire to assess student perceptions of group cohesion, communication, and affective expression. The findings appear to support the idea that social presence is a predictor of student satisfaction in online courses, but it is important to note that there is less research to demonstrate the relationship between social presence, student interaction, and student performance. This may, however, be in part a function of the weakness of self-reported survey data in accurately depicting online social presence, as the researcher takes care to point out.
Hawkins et al. (2013) used survey data to rate the quality, frequency, and type of student-teacher interaction in an online, asynchronous high school learning environment. The types of teacher interaction were classified as either procedural, feedback, or social.
The researchers sought to examine the relationship between student-teacher interactions, course completion, and performance. It was hypothesized that there would be a positive correlation between the interactions and course completion, as well as between interactions and course performance. However, the study only revealed a significant positive relationship between interaction and completion; no significant relationship was found between interaction and performance, although the researchers note that this could have been due to limited variation in the final grades of respondents.
Slightly contradictory findings about the complex role of student engagement and achievement emerged in a more recent study, albeit with an older and demographically different population of students. According to Im and Kang (2019), variability in achievement may also be described as a function of the extent to which students feel engaged and compelled to participate. The researchers surveyed 1,832 undergraduate students of an online university in Korea using a questionnaire specifically developed for their study. They found that participation was most strongly correlated with overall learner satisfaction, and that participation was largely impacted by perceptions of student self-efficacy. In addition, student participation did impact student achievement.
Still, the aforementioned research on social presence and student learning experiences are limited to older students and rely predominantly on self-reported survey data. Indeed, even the validity of the COI Survey has not been established with younger student populations. It is therefore difficult to extrapolate themes about social presence and perceived learning because the body of research on elementary and middle school students in OLEs is so limited. Broderson and Melluso (2017) analyzed 162 studies pertaining to online learning with the intent to identify common conclusions regarding the impact of K-12 online and/or blended learning programs on academic outcomes. Out of the initially identified studies, only 17 of them fit the criteria the researchers were looking for in their case study, and even fewer (only seven) were identified to have used a rigorous enough methodology to be included in the summary of findings.
Social and Emotional Competencies
Further complicating the understanding of social presence is the related, if not synonymous, concept of social competencies. Yu (2014) discussed social, emotional, and technical competencies as prerequisites to being successful in online learning and in reducing the attrition rate in online postsecondary courses. While some studies have not been able to establish a correlation between social presence and achievement (Hawkins et al., 2013; Lowenthal, 2012), others have shown positive relationships between social and emotional competencies and achievement (Berenson et al., 2008; Yu, 2014). Social competencies are considered to be the set of skills that help build, maintain, and manage social situations and interpersonal relationships, and emotional competencies represent the set of skills that allow one to reflect upon, identify, describe, and effectively manage one’s emotions (Yu, 2014). Picciano and Seaman (2007) reinforce the notion that social and emotional competencies are important, and use their national survey data to emphasize the importance of social and emotional development as a key component of student readiness to participate in online learning.
Even in traditional models of instruction, there is a growing body of evidence to suggest that social and emotional skills have intrinsic value in the classroom because of their impact on academic, social, and emotional outcomes for students (Jones et al., 2017). An SEL framework developed by Jones identifies three classifications for SEL skills: social/ interpersonal skills, emotional processes, and cognitive processes (Jones et al., 2017). Cognitive regulation consists of goal-directed skills and behaviors. Emotional processes are the set of skills by which students can regulate, identify, understand, and express a range of emotions, while social and interpersonal skills help students navigate social interactions in a positive manner. (Jones et al., 2017). While outcome research based on SEL programs have largely been conducted in face-to-face learning environments, SEL skills, as evidenced in part by measures of emotional intelligence, have been correlated with higher GPA (Berenson et al., 2008; Yu, 2014) and improved levels of student satisfaction (Kauffman, 2015) in online classes.
Habits of Mind
Costa et al. (2020, p. 54) speak to the evolving emphasis on social and emotional skills when they contend that “a contemporary education should develop students’ understanding of conceptually big, transferable ideas and processes so that they will be equipped to apply their learning to the new (and unpredictable) challenges and opportunities they will face.” In service of this shift from an emphasis on the end result of content-area knowledge to the process by which students and teachers engage in a mutual construction of learning through the reinforcement of key social, emotional, behavioral and cognitive attributes, the Habits of Mind have emerged as a theoretical framework for outlining 16 specific dispositions within the overarching and broader conceptualization of SEL skills (Costa et al., 2020; Kallick & Costa, 2009). Costa and Kallick (2008) denote that possessing a Habit of Mind reflects the proclivity of an individual to habitually access and employ intelligent problem-solving behaviors and attitudes when faced with challenges. Thus, Habits of Mind represent an amalgamation of many skills, attitudes, and behaviors based on prior schema. Habits of Mind are based on the presumption that intelligence and skillful behaviors are malleable and acquired traits, not fixed; therefore, they require mindful and explicit instruction and practice (Atlan et al., 2017, Costa & Kallick, 2008).
The 16 Habits of Mind encompass five predominant dimensions: value, inclination, sensitivity, capability, and commitment (Costa & Kallick, 2009). Value-based habits mean that individuals can differentiate between, and subsequently select, from a repertoire of intelligent behaviors to assist them in navigating difficult tasks. Habits of inclination describe the proclivity with which individuals default to value-based habits. Sensitivity describes the ability of individuals to perceive and be aware of the appropriateness of specific behaviors. Capability habits encompass the basic skills required to employ intelligent behaviors, and commitment defines the continued effort of an individual to reinforce the continued use of mindful behaviors. Costa and Kallick’s (2000) 16 Habits of Mind are summarized in Table 2.2.
Table 2.2
Habits of Mind inform pedagogical practice by making learner behaviors and dispositions a key part of the instructional framework (Kallick & Costa, 2009). Kallick and Costa (2009) emphasize that Habits of Mind should be integrated directly into the curriculum. By so doing, the explicit instruction of these habits help change the culture of learning, shifting the balance towards a more interactive and constructivist approach and away from a mechanical, industrial-era view of education. Four student outcomes are outlined within this more contemporary conceptualization of education: content, thinking skills, cognitive tasks that require skillful thinking, and Habits of Mind. These outcomes can be illustrated as nested levels of understanding about the self as well as processes and concepts that are independent of oneself. Habits of Mind represent the largest level of understanding. It is through continued and intentional reinforcement and instruction of these attributes that students can develop the cognitive tasks (i.e. strategic thinking and planning, the ability to conduct research and resolve discrepancies) that will in turn facilitate the thinking skills (i.e. analyzing, synthesizing, inferring, drawing conclusions) that, lastly, enable students to construct an understanding and acquisition of specific content (Kallick and Costa, 2009).
Figure 2.2 Nested Levels of Student Outcomes
Universal Design in Learning
Habits of Mind represent a contemporary framework of social and emotional competencies in which the process of learning and building skills is the goal, as opposed to achieving a fixed benchmark as a mere product of learning (Costa & Kallick, 2008). This is where Habits of Mind and Universal Design in Learning can converge, and help to support students wherever they may be along the continuum of skillful behavior. When educators are designing instruction from a constructivist standpoint in order to help students develop multiple measures of student outcomes, the principles of UDL (i.e., varied and flexible opportunities for student engagement, recognition/internalization of course material, and expression of understanding) become central to the theory behind the course design. The evidence in higher education that student-content interaction is a predictor of student satisfaction (Alqurashi, 2019) provides more impetus for implementing UDL in virtual classrooms and providing a variety of materials and opportunities for engaging with the course material.
Additionally, UDL is necessary to ensure that online programming is accessible to students with disabilities (Kirkpatrick, 2015). Indeed, it is interesting to note the intersection of socialization even with regards to organizational change and a shift to UDL. Kirkpatrick (2015) describes the implementation of organizational changes in education as a diffusion of innovations that emphasize social processes over technical ones. In other words, the evolution of online learning environments under a UDL framework is in large part dependent upon a systemic, holistic approach that engages students, staff, and administrators in mutually satisfying and beneficial initiatives, and requires innovative leadership geared towards continuous improvement. “Organizations should diffuse innovations slowly, on trial bases, in order to garner support incrementally while simultaneously allowing organizations to engage early problems and handle them before the entire organization becomes involved” (Kirkpatrick, 2015, p. 287).
In his research, Vadell (2013) sought to operationalize some of the best practices for gradually implementing systemic changes in order to adopt UDL in online instruction. Shifting education online allows for a more personal approach to learning that is dependent on content mastery instead of the time-based/age-dependent sequence of face-to-face learning. Continuous assessment and feedback is an important aspect of a personalized learning experience online. Adopting a specific learning management system is also key to providing a centralized environment within which to anchor the learning activities and student engagement. This requires that students are oriented to the online environment, and provided support in acclimating to the new platform. While certainly this personalization of learning in virtual spaces can be challenging and costly, the alternative is even greater costs and expenditures due to outsourcing. The proportion of students who are engaging in online learning in K-12 is likely to continue increase, and will further necessitate the reimagination of educational infrastructure based on the needs of communities and their students.
One could hypothesize that tools used to assess social and emotional competencies through the Habits of Mind framework could also clarify the overall picture and conceptualization of the multiple presences of Community of Inquiry, and thereby help researchers identify ways to manipulate both constructs through equitable, evidence-based online programming. If Habits of Mind and social and cognitive presences are connected and fluid characteristics that can be improved based on teacher behaviors and course design, and if it has been established that social and emotional competencies do indeed affect student outcomes, then it stands to reason that there are pedagogical approaches that could simultaneously improve students’ readiness for online learning as well as improve actual and perceived outcomes of learning and achievement (see Figure 2.3).
Figure 2.3 Hypothetical Model
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I would like to include perceived learning as part of my Data-driven Improvement Process (DDIP) which is carried out at the end of each unit of study.
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