Analysis of Student Perceptions of The Psychosocial Learning Environment In Online And Face-To-Face Career And Technical Education Courses

Online secondary education is growing in popularity in Washington state and around the world. Flexible scheduling and expanded learning opportunities make online learning a popular choice for high school students with a variety of educational needs and personal circumstances (Hart, 2012). In addition to offering students moreeducational choices, online learning may help school districts provide opportunities that may not otherwise be available. According to a 2013 report from the U.S. Department of Education, “Educational systems are under increasing pressure to reduce costs while maintaining or improving outcomes for students” (Bakia,Shear, Toyama, & Lasseter, 2012, p. v). In order to meet ever increasing demands with fewer resources, school districts around the country are looking at online education as a viable alternative to face-to-face classes, and online secondary education programs are growing as a result. In the 2009-2010 school year it was estimatedthat 1.5 million kindergarten through 12th grade (K-12) students took part in some type of online learning experience in the United States, and that number isexpected to grow (Wicks, 2010). While online learning continues to increase in secondary education, there is still little research describing student perceptions of how these courses compare with face- to-face courses in terms of the psychosocial learning environments (Bakia et al., 2012).

Career and technical education (CTE; formerly referred to as vocational education) provides learning opportunities for students with a focus in occupational endeavors. As cited in the Carl D. Perkins Act of 2006, CTE is defined as

CTE programs fall under the umbrella of one of the following eight areas of study: agricultural education, business education, marketing education, family and consumer sciences, trade and industrial education, health sciences, engineering and technology education, or technical education (Gordon, 2014).

Ninety-four percent of high school gradu-ates have completed CTE courses, according to the National Center for Education Statistics (2009). Career and technical education is generally characterized as vocational education, or education that prepares learners for careers that may not require a baccalaureate degree. However, because CTE courses commonly include laboratories and extensive hands-on learning, they may not appear to be conducive to online learning.

CTE courses emphasize problem-based learning, collaboration, active learning, skill development, and career exploration (Threeton, 2007). Studies indicate a learning environment that includes these and similar psychosocial elements improves student efficacy (Dorman, 2001). Integrating CTE and core topics with authentic problem solving in subjects such as engineering and science may provide students with greater motivation to learn and succeed (Berry et al., 2004). Com-bining CTE programswith an online learning platform may have the potential to further support student success by providing a greater range of educational opportunities and learning style options.

Supporting students through teacher interaction, student collaboration and communication, extending learning outside of class, problem solving, and inquiry learning has been shown to improve student achievement (Brewer, 2004; Rovai, 2002). These supportive practices, when considered in the design of high school curricula, may improve student learning in both online and face-to-face environments. Understanding how students perceive the psychosocial learning environment of CTE courses in the context of both online and face-to-face venues is an important step in developing curricula that will support student learning and achievement.

The purpose of this study was to analyze student perceptions of the psychosocial learning environment in online and face-to-face high school CTE courses to examine the efficacy of the psychosocial environment from a student’s perspective.

The following research questions were addressed to frame this study:

• RQ1: How do students perceive the psycho-social environment in face-to-face career and technical education courses?

• RQ2: How do students perceive the psycho-social environment in online career and technical education courses?

• RQ3: How do student perceptions of the psychosocial learning environment in career and technical education differ for students in online courses compared with students in face-to-face courses?

Bandura (1977) stated that individual perceptions impact self-efficacy, and self-efficacy ultimately determines an individual’s coping mechanism, effort, and the sustainability of that effort when facing learning challenges. Supporting that model, studies conducted by the Bill and Melinda Gates Foundation (2012a, 2012b) suggest that student perceptions of instruction are predictive of student achieve-ment. These studies have found that student perceptions are more predictive of achievement gains than classroom observations or standardized testing measures. In addition to more traditional measures of achievement, surveys of student perceptionsof the learning environment and instruction may help professional educators determine how to improve practices and ultimately improve student outcomes (Bill & Melinda Gates Foundation, 2012a).

Although online learning has increased in popularity in K–12 education nationwide, there is little empirical research indicating how students perceive the psychosocial learning environment in these classes compared with face-to-face classes. With an increased emphasis on online learning at the high school level, understanding how students perceive the psychosocial learning environments in secondary online and face-to-face CTE courses may aid educators to ensure that student support is incorporated within course design (Patrick & Powell, 2009). This study analyzes and compares student perceptions of the psychosocial environments in online and face-to-face CTE courses.

Distance learning can be defined as “improved capabilities in knowledge and/or behaviors as a result of mediated experiences that are constrained by time and/or distance such that the learner does not share the same situation with what is being learned” (Caglar, 2013, p. 10). According to Holmberg (1986),

Online learning, a corollary of distance learning, takes place via the Internet using web-based delivery models in a structured learning environment where students and teachers are geographically separated (Watson, Murin, Vashaw, Gemin, & Rapp, 2012).

Online programs may be offered through synchronous or asynchronous models, and 74% of public school online enrollments are at the high school level (Watson et al., 2012). Both synchronous and asynchronous models are currently being used in the various K–12 programs, and multiple settings are being used including local school buildings to allow access to the necessary technology (Kronholz, 2011).

CTE courses play an important role in the development of individual students and the future of American society (Brewer, 2004). By addressing industry skills, leadership, 21st century skills, and the integration of academic knowledge, CTE courses have become an important element in most high schools today (Stone, 2007). However, ensuring CTE opportunities are available for all students can be challenging with increased graduation requirements in academics, increasing costs, and lack of available teachers with specialized CTE training (Fletcher, 2006). Offering CTE courses from a distance through an online medium may provide the opportunity for more students to participate in these programs, giving more students relevant career skills that are needed by employers (Brown, 2010). As the alliance between online learning and CTE moves forward in traditional middle and high school education, the unique histories make the merger unprecedented (Metz, 2010).

CTE courses boast a hands-on, applied, and experiential learning approach that may not appear to be compatible with online learning (Benson et al., 2005; Brewer, 2004; Manley, 2011). Some CTE courses, such as those in business and management, finance, computer science, and communications may be easily adapted to an online environment (Alonso, Manrique, Martinez, &Vines, 2011; Kuruvilla, Norton, Chalasani, & Gee, 2012).

However, with hands-on elements often associated with CTE programs in agriculture, health sciences, engineering, and manufacturing, the use of hybrid models, virtual laboratories, and online simulations are often effective for enabling CTE students to experience online learning (Blackinton, 2013; Potkonjak, Jova- novic, Holland, & Uhomoibhi, 2013). Accord- ing to Potkonjak et al. (2013), a virtual laboratory can be used in place of or as a pre- cursor to a real laboratory and can be reconfigured and adjusted much more easily than actual laboratory equipment. Hybrid courses, or those that have both online and face-to-face elements, may also enhance the online learn- ing experience for students when hands-on guidance and practice are necessary learning components (Blackinton, 2013).

Online CTE courses may use a variety of learning management systems and may include discussion forums, synchronous chats, computer-based simulations, video tutorials, and technology-based assessments (Benson et al., 2005; Lewis, 2011). A 2001 study of online CTE nursing students found that one significant difference between online and face-to- face students was the degree to which they felt socialized into the nursing profession. According to the study, students in the online program felt they were more socialized than those students in a face-to-face learning environment. Socialization into a professional field is an important component of CTE, and it helps shape professionals that will continue to be connected to others within their chosen career field (Benson et al., 2004).

The psychosocial learning environment in an online course is represented by the communication and social context developed within the course and among its participants (Walker & Fraser, 2005). Within any educational environment, certain factors are of primary concern in the discussion of potential for both student achievement and school success; these factors include connectedness and support through relationship building, students’ expectations for learning, student autonomy, learning activities, and academic motivation (Anderson- Butcher, Amorose, Iachini, & Ball, 2012; Walker &Fraser, 2005). Analyzing how students perceive the factors within the learning environment will help promote more student friendly, psychosocially rich learning (Fraser & Fisher, 1982).

Gentry and Owen (2004) describe learning environments in terms of appeal, challenge, meaningfulness, academic self-efficacy, and choice. Their research indicates that these constructs are central to effective learning. Education is most effective when the information presented is challenging, relevant, meaningful, interesting, and sparks the imagination. Consideration of these factors in a learning envi- ronment represents “an important aspect of quality education” (Gentry & Owen, p. 21).

According to Walker and Fraser (2005), the psychosocial learning environment can be divided into seven categories or scales: instructor support; student interaction and collaboration; personal relevance; authentic learning, or the reality of content covered in the class; active learning; student autonomy; and enjoyment.

Instructional practices that facilitate the online psychosocial learning environment are critical to promoting student success (Walker & Fraser, 2005). The learning environment plays an important role in how and why students construct meaning and how effective their learning is (Gentry & Springer, 2002). Constructing knowledge through collaboration, authentic and active learning, personal relevance, autonomy, and instructor support can help students learn more effectively and retain the information (Renzulli, 1994; Walker & Fraser, 2005).

Students’ perceptions of the psychosocial learning environment and how the environment helps them feel connected impact the way students learn within that environment (Rovai, 2002). According to Caglar (2013), a feeling of alienation has a considerable impact on a student’s ability to learn, and negative attitudes toward the learning environment will obstruct the learning institution from achieving its goals.

Rodgers (2006) found that students’ descriptions of their own learning through student-teacher dialog play an important role in meeting learners’ needs and building trust and community. In addition to the sense of community and connectedness, there are a variety of factors that influence how students perceive the learning environment including technology, communication, learning and teaching styles, and student participation (Fraser, 1998; Leping, 2011). Fraser and Giddings (1992) found that students’ perceptions of the psychosocial learning environment may be effective predictors of student success. Greene, Miller, Crowson, Duke, and Akey (2004) established that students’ perceptions of their learning environment affected their self-efficacy and ultimately their motivation to learn. A Bill and Melinda Gates Foundation study (2012b) recognized that student feedback of instruction and the learning environment was an important element for improving student achievement outcomes. As a result, understanding student perception of the learning environment is important for further study and improvement of online education (Barbour, 2008; Gates Foundation, 2012a; Walker & Fraser, 2005).

According to Entwistle, McCaune, and Hounsell (2002), learning is affected more by the perception of the instructional practices than by the method of instruction. Studies of middle and high school students suggest that when students have positive perceptions of their communications and connections in school, it correlates to higher grades and graduation rates (Anderson-Butcher et al., 2012). Positive student perceptions of the online psychosocial learning environment may lead to greater persistence and more motivation to pursue additional online courses (Lessick et al., 2013). According to Gentry and Owen (2004), designing learning environments linked to students’ perceptions may provide school improvement and enhance student achievement.

In 2012, a Washington state school district determined that a method of analyzing the quality of existing online programs was needed, and examining the psychosocial learning environment was an element of that analysis. An online survey was administered in January, 2014, to high school (Grades 9–12) career and technicaleducation students in a in an effort to make such a determination. Directors from the district contacted online students via e-mail to provide the survey link. Face-to- face students were given the survey link in classes by their teachers. Student responses were anonymous and no personal identifying information was included in the final survey results.

The population for this study included all high school students currently taking an online or face-to-face CTE class (N = 745) within the Washington State school. For confidentiality, the school district was not named in the reporting of this study. Students were identified by district officials based on courses that were offered during the semester. Surveys were dis- tributed to all CTE students in the courses listed in Table 1.

This study used a modified version of the Distance Education Learning Environment Survey (DELES) designed to gather information about students’ perceptions of theonline education environment. The survey included six psychosocial scales and a seventh scale for enjoyment. Although the survey was designed to be used with postsecondary online students, Metz (2011) suggested the survey would be suitable for high school students with appropriate modifications. The items were revised slightly to accommodate the differences in commonly used terminology between high school and postsecondary and between online and face-to-face learning environments. The psychosocial scales and their related items are outlined in Table 2.

Permission to use the DELES survey was received from the original survey designer, Scott L. Walker. The survey contains 42 Likert-scale items and seven descriptive and demographic items. The results of a factor analysis determined the categories that ultimately defined each of the seven scales. Using Cronbach's alpha coefficient, the original survey’s reliability for each scale ranged from 0.75 (acceptable) to 0.92 (excellent; Walker &Fraser, 2005).

The independent research variable for RQ1 and RQ2 is whether respondents took the course via a face-to-face or an online venue and the responses to the 42 survey items. The dependent variable consisted of the student perceptions of the psychosocial learning environment.

The first independent variable for RQ3 was the course format: online or face-to-face. The second independent variable was student perceptions of the psychosocial environment as determined by the sum of the mean score for each scale. To determine overall perceptions scores, the sum of the means for each scale was calculated. The dependent variable for RQ3 was the difference, if any, in perceptions in the seven scale areas between the online and face- to-face students.

For this study, the researchers slightly modified the survey items to accommodate high school students. To ensure validity of the modified survey, the researchers conducted a new factor analysis. Table 3 provides the results of the revalidation for this study. Alpha reliabili- ties range from acceptable (α = 0.76) to excellent (α= 0.93).

The researchers analyzed the means, medians, and standard deviations in each of the scale areas from online and face-to-face CTE student responses to address the first two research questions addressing students’ perceptions of the psychosocial learning environment in face-to-face and online CTE courses. The researchers then compared differences in the sum of the means for each of the seven scale areas between face-to-face and online student data to determine if differences exist. Because of high levels of skewness in 8 of the 14 scales, A Mann-Whitney U test was applied to measure variability and compare the sum of the means for each of the scale scores between online and face to face.

The Distance Education Learning Environment Survey (DELES) was distributed to 745 (N = 745) students. Of the total 745 students, 179 were online students and 564 were face- to-face students. A total of 584 (n = 584) student responses were collected, with 543 from students taking a face-to-face class and 41 from online students. A population of 800 requires a minimum response rate of 363 to indicate a valid sample (Bartlett, Kotrlik, & Higgins, 2001), thereby making the sample valid.

For each individual survey item, students were asked to choose from the following possible responses: 1 = never, 2 = seldom, 3 = sometimes, 4 = often, and 5 = always. Responses for each item were totaled and averaged to arrive at the mean scores. Averages for individual items within each scale were then summed providing an overall sum of the means for each scale.

To address the first and second research questions regarding how students perceive the psychosocial learning environment in face-to- face and online CTE classes, descriptive statistics were analyzed for each scale. Skewness was analyzed to determine normality of the curve for each of the scales. According to Bulmer (1979), skewness less than -1 or greater than 1 are considered highly skewed; skewness between -1 and -1/2 or between 1/2 and 1 are moderately skewed; and skewness between -1/2 and 1/2 are approximately symmetric.

Instructor Support. Eight items combined to form a reliable scale of student perceived level of instructor support. With possible responses to each of the eight items ranging from 1 to 5, the possible sum of the scale scores ranged from 8 to 40, with larger values indicating higher levels of perceived instructor support. The sum of the means for face-to-face students was 33.3 (M = 33.3, SD = 5.6), with a moderately high skew of -.944. The sum of the means for online students was 32.7 (M = 32.7, SD = 6.5). Further, these data show a high skew of -1.174.

Student Interaction and Collaboration. Six items combined to form a reliable scale of perceived level of interaction and collaboration among students. The possible sum of the scale scores ranged from 6 to 30 with larger values indicating higher levels of perceived student interaction and collaboration. The sum of the means for face-to-face students was 21.7 (M = 21.7, SD = 5.1). These data show a mod- erate skew of -.542. The sum of the means for online learners was 14.3 (M = 14.3, SD = 7.2) and skew of .291, indicating approximate symmetry for this scale.

Personal Relevance. Seven items com- bined to form a reliable scale of student perceived level of personal relevance. The possible sum of the scale scores ranged from 7 to 35, with larger values indicating higher levels of perceived personal relevance. The data show a sum mean of 24.6 for face-to-face students (M = 24.6, SD = 5.6). The skew mea- sured at -.280 indicating approximate symmetry for this scale. The sum of the means for online students was 24.2 (M = 24.2, SD = 6.9) with a skew of -.752, indicating a moderately negative skew.

Authentic Learning. Five items combined to form a reliable scale of perceived authentic learning. The possible sum of the scale scores ranged from 5 to 25, with larger values indicating higher levels of perceived authentic learning. The sum of the means for face-to-face learners was 17.8 (M = 17.8, SD = 4,0) and a skew of -.087 indicating a normal distribution. The sum of the means for online learners was 17.4 (M = 17.4, SD = 4.4). Skew for the authentic learning scale was moderate at-.534.

Active Learning. Three items combined to form a reliable active learning scale. The possible sum of the scale scores ranged from 3 to 15, with larger values indicating higher levels of perceived active learning. The sum of the means for face-to-face students was 11.3 (M = 11.3, SD = 2.1) and moderately low skew of -.482. The sum of the means for online students was 12.5 (M = 12.5, SD = 2.2) with a high skew of -1.241.

Autonomy. Five items combined to form a reliable scale of perceived autonomy. The possible sum of the scale scores ranged from 5 to 25, with larger values indicating higher levels of perceived autonomy. The sum of the means for face-to-face students was 20 (M = 20.0, SD = 3.5). Skew for this scale was moderate at-.596. The sum of the means for online students was 21.8 (M = 21.8, SD = 3.4). Skew for the autonomy scale was high at -1.996.

Enjoyment. Eight items combined to form a reliable scale of perceived enjoyment. The possible sum of the scale scores ranged from 8 to 40, with larger values indicating higher levels of perceived enjoyment. The sum of the means for face-to-face learners was 28.6 (M = 28.6, SD = 7.4). The skew for the enjoyment scale is moderately low at -.441. The sum of the means for online learners was 24.1 (M = 24.1, SD = 8.4) and a moderately low skew of -.447.

For Research Question 3, the researchers sought to compare online and face-to-face student perceptions within the seven scale areas. Based on Bulmer’s principles, the scales of instructor support, student interaction and collaboration, and autonomy showed a moderate skew in the face-to-face student data. The online student data show high skewness levels in the scales instructor support, active learning, and autonomy. The online data also show moderate skew in the scales of personal rele- vance and authentic learning. Because the Mann-Whitney U test makes no assumption about the shape of the distribution and regards the scales as ordinal (rank) rather than interval level of measurement, it was utilized for this study.

Instructor Support. Face-to-face student perceptions showed an average rank of 293.01, and online student perceptions showed an average rank of 285.70. The results of the Mann-Whitney U test indicate there is no sig- nificant difference in students’ perceived levels of instructor support, U = 10852.5, z = -.268, p > .05.

Student Interaction and Collaboration. Face-to-face student perceptions showed an average rank of 304.04, and online student perceptions showed an average rank of 139.61. The results indicate there is a significant dif- ference in students’ perceived levels of interaction and collaboration, U = 4863, z = 6.03, p < .05, with face-to-face students indicating a higher perceived level of interaction and collaboration with classmates.

Personal Relevance. Face-to-face student perceptions showed an average rank of 292.21, and online student perceptions showed an average rank of 296.34. The results of the Mann-Whitney U test indicate there is no significant difference in students' perceived levels of personal relevance, U = 10974, z = -.151, p > .05.

Authentic Learning. Face-to-face student perceptions showed an average rank of 293.13, and online student perceptions showed an average rank of 284.17. The results indicate there is no significant difference in students’ perceived levels of instructor support, U = 10790, z = -.329, p > .05

Active Learning. Face-to-face student perceptions showed an average rank of 285.65, and online student perceptions showed an average rank of 383.21. The results of the Mann-Whitney U test indicate there is a significant difference in students’ perceived levels of this scale, U = 7412.5, z = -3.62, p<.05, with online students indicating a higher level of perceived active learning.

Autonomy. Face-to-face student perceptions showed an average rank of 285.36, and online student perceptions showed an average rank of 387.09. The results of the Mann-Whit- ney U test indicate there is a significant difference in students’ perceptions of this scale, U = 7253.5, z = -3.74, p <.05, with online students indicating a higher level of perceived autonomy.

Enjoyment. Face-to-face student perceptions showed an average rank of 298.61, and online student perceptions showed an average rank of 211.62. The results of the Mann-Whit- ney U test indicate there is a significant difference in students’ perceived levels of enjoyment, U = 7815.5, z = -3.187, p <.05, with face-to-face students indicating a higher level of enjoyment in the class environment.

An analysis of the instructor support scale reveals that students in both venues felt their instructors were supportive, responsive, and prompt. Over 75% of face-to-face students responded with a 5 (always) or 4 (often), while 76% of online students reported the same. Research reports that support from instructors is an important course element from a student’s perspective (Lemley, Schumacher, & Vesey, 2014; Sahin, 2007). Prompt feedback and the encouragement of participation lead students to perceive the learning environment as more positive, and student performance is enhanced in a supportive environment (Garrett Dikkers, Whiteside, & Lewis, 2013). Often assumed to be a missing element in online courses, evidence of instructor support is an important finding for online course developers and those who are skeptical of online courses (Swan, 2003).

Analysis of the student interaction and collaboration for face-to-face students reveals a mean score of 21.7 for this scale, while online students reported a low mean score (M = 14.3) with over 50% responding with a score of 2 (seldom) for 5 of the 6 scale items. This indi- cates that online teachers and course develop- ers must find ways to encourage students to work in teams and communicate during online courses. For online students, interaction and collaboration may seem more challenging, but online course developers can incorporate strategies to encourage students to work together and communicate about their learning (Beckem & Watkins, 2012). Instructors and course developers must be more deliberate about creating an online environment that includes rich interaction and collaboration (Lynch, 2004). As social networking and digi- tally enhanced collaboration and communica- tion tools are becoming more widely available in schools, there is room for improvement to ensure these opportunities are clearly and intentionally available to students (Pearson, Carmon, Tobola, & Fowler, 2009).

Although relevance is often viewed as a primary feature of CTE courses, the scale earned only moderate marks from both groups (M = 24.56 face-to-face, M = 24.2 online). Although the importance of relevance is widely understood in CTE, integrating relevance is not easily accomplished, and these data show that teachers and course developers need to improve upon this element so students will begin to better recognize how their course competencies relate to careers and life.

Authentic learning is also a source of pride for many CTE educators; however, both groups reported moderate levels regarding whether or not the content reflected the real world of work. Along with relevance, authentic learning is crucial in CTE courses and is often what sets CTE apart from other courses (Brewer, 2004). Whether in a classroom or online, workforce advisory committees CTE should be guiding programs in public education, and authentic learning should be a natural outcome of the partnership with business and industry (Leary, 2012).

Active learning was rated only moderately by the majority of students in the face-to-face environment as evidenced by the mean score (M = 11.3) for this scale, where the possible scores ranged from 3 to 15, but moderately high by the majority of students (M = 12.5) in the online environment. This indicates that online students feel they explore their own learning strategies, seek their own answers, and solve their own problems in their online courses. This may be because online students often become independent learners out of necessity (Association for Career and Technical Education, 2010).

With over half of the students reporting 5 (always) and 4 (often) responses, the auton- omy scale resulted in a relatively high percentage compared with the previous three scales for face-to-face students. Along with active learning, it is not surprising that the scores for the autonomy scale were also relatively high for online students (M = 21.8). Possible scores for this scale ranged from 5 to 25. With most or all work completed away from an instructor, students’ sense of self-reliance is heightened in an online environment (Seiver & Troja, 2014).

Analysis of data for the enjoyment scale shows that face-to-face students moderately enjoyed their CTE course, as approximately 56% of students scored 5 (always) or 4 (often) on the items in the enjoyment scale. Although online students indicated they were satisfied with the course, the scores for the enjoyment scale were lower overall for online students (M = 28.2), where possible scores ranged from 8 to 40. Students rated “I am satisfied with this class” high as compared with the other items in this scale, with approximately 80% of students rating a 3 or above for this item. This indicates that although student interaction, collaboration, and relevance were not common online, the online environment was still able to meet students’ needs. Some of the primary reasons students take online courses are convenience and flexibility, and students may not consider interaction and collaboration as an important component when deciding to take a class online (Barbour et al., 2011).

For Research Question 3, the researchers sought to compare online and face-to-face student perceptions within the seven scale areas. As with earlier studies regarding student satisfaction comparisons in online and face-to-face environments, student perceptions in both environments differed in some key areas, but they were quite similar in other areas.

The results of the Mann-Whitney U test indicate there is no significant difference in students’ perceived levels of instructor support, personal relevance, or authentic learning. However, results indicate that there are signif- icant differences in students’ perceived levels of interaction and collaboration, active learning, autonomy, and enjoyment. The higher means for online students in active learning and autonomy may be byproducts of the nature of the online learning environment, andface- to-face instructors may take note and attempt to replicate some similar strategies of online learning. Conversely, because online learners reported a significantly lower level of enjoy- ment, online course developers and instructors may attempt to simulate more in-class type strategies, either through replication or simulation.

Based on the results of this study, it is recommended that school districts and other educational institutions continue to explore the use of an online platform for CTE courses. It is further recommended that CTE professionals review their current delivery methods and investigate options for increasing the opportunities for students to collaborate and communicate with peers as part of the learning environment whether it is online, face-to-face, or a combination of the two. Relevance and authentic learning, two areas where both environments show the need for improvement, should be continually reviewed to ensure the learning environment is enriched with authentic content.

This and previous studies of online learning in secondary education find that instructor support and interaction and collaboration are central to student satisfaction (Johnson, Cascio, & Massiah, 2014). It is recommended that more research be conducted with various psychosocial environments to determine the effect of instructor support along with collaboration and interaction on student satisfaction and achievement as identified by course completion, final grade, or standardized test results.

Although this study specifically looked at CTE courses in both environments, additional studies looking at other disciplines would be beneficial to clearly identify the benefits and drawbacks to offering courses both online and face to face. A future study should be undertaken to determine if enhanced instructor communication increases student engagement in an online environment in CTE. Additionally, it is recommended that a study be conducted to determine the impact on student learning of teacher professional development including mentoring and online course delivery instruction.