The Influence of Personality and Chronotype on Distance Learning Willingness and Anxiety among Vocational High School Students in Turkey

There are many studies related to distance learning. Willingness and anxiety are important variables for distance learning. Recent research has shown that anxiety and willingness towards distance learning are moderated by personality. This study sought to investigate whether distance learning willingness and distance learning anxiety are associated with age, gender, occupation, chronotype and personality in a Turkish vocational high school students sample. Two measures of individual differences were implemented: chronotype (morningness/eveningness preference) and BIG-5 dimensions (agreeableness, conscientiousness, extraversion, neuroticism, and openness). Seven hundred and sixty-nine vocational high school students from Turkey filled out a self-administered questionnaire. Evening types, older, and female students had higher distance learning willingness scores than morning types, younger, and male students. No significant difference was found between chronotype groups with respect to distance learning anxiety. Furthermore, extraverted students reported a lower distance learning anxiety. Openness to experience was associated with high distance learning willingness. We conclude that evening types may benefit from distance learning more than other types.


The Influence of Personality and Chronotype on Distance Learning Willingness and Anxiety among Vocational High School Students in Turkey
Introduction One of today's most common learning applications is distance learning and it is continuing to become widespread. Distance learning (DL) is a learning application where students learn by using learning material and communication technology when instructors and students are separated by time and/or location (Moore & Kearsley, 2005). For these reasons, DL students may have more self-directed, self-oriented, and independent learning habits and a higher level of information technology skills. In this respect most of the DL students are university students and they are older than face-toface students (Hunt, 2010;Mupinga, 2005;Tucker, 2003). So DL for adults is not a new application but DL in high schools has been growing in recent years (Rice, 2006). In the United States, approximately 700,000 elementary and secondary education students (1.1 % of all K-12 students) were enrolled in DL in 2007 (Picciano & Seaman, 2009).
Open high school in Turkey was implemented in 1992 (Demiray & Sağlık, 2003). Open high school programs or open education systems have the ability to offer quality education to a large number of students (Latchem, Özkul, Aydin, & Mutlu, 2006). Open

K-12 Distance Learning
There are different terminologies in the literature related to K-12 level DL. Some of them are K-12 DL, "virtual schools" and "cyber schools". We chose to use the K-12 DL concept in the study because of its widespread use. Many studies are addressing DL in adults, but there are limited studies of theK-12 level (Barbour & Reeves, 2009;Cavanaugh, Barbour, & Clark, 2009). With K-12 level application, DL began to cater for all age groups (adolescents and adults; Rice, 2006). At the K-12 level, although there are a limited number of articles, DL hasbeen studied mostly in the United States and Canada (Barbour & Mulcahy, 2008;Picciano & Seaman, 2009;Rice, 2006;Sheppard, 2009). Also especially the United States and Canada, K-12 level DL is increasing and spreading every day (Allen & Seaman, 2013;Barbour, 2013;Demiray & Sağlık, 2003;Smith, 2009). In developed countries such as USA and Canada, K-12 DL is used to provide the opportunity for students with learning disabilities. Other reasons in developing countries are students learning in different places and at different times, overcrowded classrooms, lack of quality teachers and school infrastructure (Barbour, 2013;Barbour & Mulcahy, 2006;Cavanaugh & Clark, 2007). In developing countries, such as Turkey, K-12 DL is used for economic, cultural, and social development (Moore & Kearsley, 2005). Another reason for the increase and spread of K-12 DL may be that students are more successful in DL than in face-to-face learning (Cavanaugh, 2001;Cavanaugh, Gillan, Hess & Blomey, 2004;Rice, 2006 K-12 DL students are typically working adults and mostly women (Moore & Kearsley, 2005), students with disabilities, and students from rural areas (Berman & Tinker, 1997). In K-12 DL and other DL applications, the number of participants from rural areas is higher than from urban areas (Picciano & Seaman, 2009). One of the reasons may be the more difficult access to schools and qualified personnel in rural areas. In addition, some studies stated that DL students from rural areas are at least equal or even more successful than those in the city center (Barbour & Mulcahy, 2006Sheppard, 2009). In this aspect, achievement is another reason why DL could be chosen by participants from rural areas.
DL (especially asynchronous DL) offers participants learning with their preferred speed, time and style (Roblyn, 1999). In this aspect, DL is developing critical and creative thinking, time management, problem solving skills, and independent learning habits (Barker & Wendel, 2001). Despite these benefits, DL is not the most effective choice in all situations, especially not in novice students (Cavanaugh, Gillan, Kromrey, Hess, & Blomeyer, 2005) and digital immigrants (Prenksy, 2001). When compared to face-toface learning, many students are not familiar with DL. These students, who faced DL for the first time, were defined as novices (see Cornacchione, Lawanto, Githens, & Johnson, 2012;Moore & Kearsley, 2005). Conrad (2002) found that novice students express fear and anxiety when they start DL. Higher dropout rates may result from anxiety and may affect distance learning willingness (DLW; Cavanaugh, Barbour, & Clark, 2009). Hara (2000) found that technical and communication skills and DL experience are important factors for a DL student's anxiety. Williams (2007) found that DL students prefer traditional face-to-face learning more than DL. On the contrary, Wang (2007) found that DL students were pleased with DL and willing to continue. For successful DL, a student's distance learning anxiety (DLA) and DLW are important variables (Horzum & Çakır, 2012;Jegede & Kirkwood, 1994) and may vary according to students' characteristics.
One advantage of DL is the independent time management so students can learn at their optimal time of day. This is in strong contrast to the usual early morning schedules at school (Hurd, 2007). Evening type students with regularly scheduled school learning have more problems (emotional problems, timing of sleep, learning success, etc.; Gau, Shang, Merikangas, Chiu, Soong, & Cheng, 2007). Recent research showed that chronotype had a significant influence on school and university achievement (Beşoluk, 2011;Fabbri, Antonietti, Giorgetti, Tonetti, & Natale, 2007;Randler & Frech 2006) with earlier chronotypes being at an advantage. Thus eveningness should be related to DLW.
Chronotype is also related to personality factors as measured by different inventories (for an overview see Tsaousis, 2010 andAdan et al., 2012). In the current literature on DL, two of the most widely recognized and applied personality models are the Myers-Briggs (MBTI) and the Big Five personality model (BIG-5). MBTI profiles are known to have strong implications on learning style, and BIG-5 represents the dominant conceptualization of personality in the current literature (Kim, 2011;Kim &Schniederjans, 2004). Research on personality and chronotype indicated that eveningness is related to extraversion, impulsivity, novelty seeking, depressive symptomatology as well as openness and, to smaller extent, psychoticism (psychopathology) while morningness is related to conscientiousness, agreeableness, persistence, and emotional stability (see Adan et al., 2012;Tsaousis, 2010).
There is only limited research onchronotype and other personality dimensions in DL.
Individual differences in personality influence outcomes and experiences of DL. For example, students with lower conscientiousness failed their courses more often (Santo, 2001) and high emotional stability was related to persistence (Kemp, 2002). High introversion was related to preference and participation in DL (Moore & Kearsley, 2005). Anxiety scores of the DL students are relatively moderate or higher and anxiety levels didn't change significantly overtime (Bolliger & Halupa, 2012;MacGregor, 2002). Önder, Horzum, and Beşoluk (2012) worked with face-to-face and blended learning students. They noticed the importance of the synchronicity between learning time and circadian preference. In their research it was found that students' performance was enhanced when teaching was performed in sync with students' chronotype. Evening types in face-to-face learning students expressed a higher DLW and they chose DL lessons more often than morning types (Jovanovski & Bassili, 2007). Horzum, Önder, and Beşoluk (2014) found no difference in online learning students' achievement according to chronotype. Furthermore, Luo, Pan, Choi, Mellish, and Strobel (2011) found that students' chronotype affected their individual daily time schedules for DL. Studies on cognitive abilities and performance showed evidence for a synchrony effect, that is, evening types should prefer and perform better in later lessons and morning types should prefer and perform better in earlier lessons (Goldstein, Hahn, Hasher, Wiprzycka, & Zelazo, 2007).
Previous research did not investigate the influence of personality and individual differences (chronotype and BIG-5) on DLA and DLW. The aim of this research is to investigate differences of the students' DLA and DLW according to age, gender, occupation, and personality (chronotype and BIG-5). We hypothesize that eveningness is associated with higher DLW.

Method
The research was based on quantitative paper-and-pencil survey methodology. Students filled out self-administered questionnaires. Data were collected by hand.

Participants
Participants voluntarily completed a questionnaire in the 2012 academic cycle. These participants were purposively sampled from Vocational Open High Schools (VOHS).
The reason for the selection of students in the VOHS is that it is the most widely spread and most preferred application in the K-12 level DL in Turkey (Horzum, 2007). Seven hundred and sixty-nine VOHS students participated, 408 (53.1%) were females. Age ranged from 14 to 44 years, 580 (75.4%) students were between 14-18 years old, and 189 (24.6%) students were between 19 and 44 years; the mean age was 17.78 (±2.29) years.
Two hundred and seventy-nine (36.3%) were employed (part time students) and 490 (63.7%) were unemployed (full time students). Two hundred and forty-two (31.5%) were from the Aegean and 527 (68.5%) from the Marmara region of Turkey. These two regions of Turkey are comparable for the rise of the sun and sunlight proportion.These two regions were selected because they share a similar longitude and similar development level.

VOHS System in Turkey
The VOHS education system lasts at least fouracademic years and eightsemesters (an academic year consists of two semesters). If one of the student's mean year-end reaches45 points and higher, theypassthe course successfully. Students who have successfully completed their course acquire credits.
There is no age restriction in VOHS. People of all ages who graduated from elementary school or dropped out from high school can apply to VOHS. In these programs, common (general cultural) field and elective courses are included. Students in the VOHS take Students' personality was measured using the BIG-5. In this study the BIG-5 is used in its 10-item short version. Short questionnaires can be good measurements when time is constrained (Burisch, 1998). The scale contains 10 items on a five-point Likert scale. It was developed by Gosling, Rentfrow, and Swann (2003) and adapted into Turkish by Günel (2010).
Older VOHS students showed a higher willingness to DL (r =.096, p = .008) and a lower anxiety (r = -.065, p = .074), extraverted students reported a lower anxiety (r = -.153, p < .001; Table 1). Table 1 Correlations between Study Variables Gender was a significant predictor of willingness but not of anxiety, CSM was associated with willingness. Age showed an effect on willingness and a trend on anxiety, extraversion was associated with anxiety, and openness was associated with willingness (
Evening orientation was related to a higher DLW, which remained significant after controlling for personality in the linear model. Similarly, evening type students had higher DLW, a finding that has been previously proposed by Jovanovski and Bassili (2007). These findings indicated that a DL program can present learning environments that are better suited to individual differences (Moore & Kearsley, 2005), especially of the late chronotype. So, for evening type students, DL is perceived as the better option.
Asynchronous DL is carried out in VOHS. One explanation of these results may lie in the nature of asynchronous DL. In DL programs, all students may set the schedule themselves, yet are able to access learning material and lessons from anywhere and anytime and learn at their own pace. Moreover, it was found that students' chronotype affected the choice of learning time in DL (Luo et al., 2011 (Beşoluk, 2011), may prefer DL environments. An interesting question might be to compare individual learning processes in DL and in scheduled school programs.
DLA was unrelated to morningness-eveningness. As anxiety was unrelated to chronotype, DL should benefit all chronotypes equally with the advantage of working/performing at one's own best time. Therefore we encourage educational institutions to implement DL programs.
Moreover, extraverted students reported lower DLA. Extraverted students have a tendency to be sociable, talkative, active, and ambitious (Kim, 2011), so they reported lower anxiety. Open-minded students reported a higher DLW. This finding is consistent with the literature: Santo (2001) found that students with higher scores on openness to experience also express positive opinions of DL and they learn effectively when taking DL (Kim & Schniederjans, 2004).
Furthermore, this study showed that age has an effect on DLW. Older students may prefer DL because most of the older students are married and work while studying.
Because they work or take care of children, it is difficult to participate in face-to-face lessons, and DL might be the better opportunity to study. Therefore, their DLW is higher. Consistent with the results of our study, Hurd (2007) found that older students prefer DL since they are learning within the context of family and work, and they need to fit learning into their time schedule and therefore prefer to study at their own pace.
However, it was found that age was also associated with anxiety. This finding is consistent with Conrad (2002). Most of the older people haven't enough information technology skills (Prenksy, 2001) to benefit from DL. In DL, students have to handle some technological devices for learning. In conclusion, this anxiety may result from older students' lack of technological skills.
In this study we found that DLA of students did not differ with respect to gender.
Consistent with the results of this study, Jegede and Kirkwood (1994) found no significant differences in students' DLA according to gender. However, it was found that women have lower DLW than men. Women who successfully perform in a face-to-face learning environment (Beşoluk, 2011) want to remain in this familiar environment and not turn towards DL.
Our study has several limitations. One of them is that participants were VOHS students.
In order to obtain a more generalized result for all high school students, similar studies are needed from open high school or open secondary school students. 720 students participated in the study. For more generalized results further research should be done with more participants. Another limitation is related to the data collection process. We used only quantitative instruments. One of the problems in findings related to DL is the use of quantitative methods (Bernard, Abrami, Lou, & Borokhovski, 2004). In addition, to increase the validity of the data, some other measures (qualitative methods) should be obtained, such as observation, interview, document analysis, and so on. Furthermore, since participation was voluntary, the sample suffers from self-selection.
Asynchronous DL is carried out in VOHS. Also similar studies can be done on synchronous DL applications or comparable studies can be done on synchronous and asynchronous applications.
In conclusion, our study contributes to the knowledge about differences in DLW and DLA according to circadian types and personality. Future work should further investigate acceptance of DL applications in relation to circadian type and personality.