Social science education students’ preparedness for problem-based hybrid learning

ABSTRACT


RESEARCH METHOD
This research is a quantitative research using explorative survey method, conducted in an even semester of 2019-2020. The research subjects were 118 students, consisting of 32 male and 86 female students, from Social Science Education Program, Faculty of Tarbiyah and Teacher Training, Universitas Islam Negeri Maulana Malik Ibrahim Malang, Indonesia. These respondents were randomly chosen from 154 fourth semester students taking social geography course.
A questionnaire was used as an instrument in this research to measure students' readiness. The questionnaire was adapted from Xiong et al. [47]. The questionnaire subsists of statements adjusted to indicators of students' preparedness in PBHL. The first indicator is the motivation aspect, with 16 items that cover interest, perception, self-efficacy, and reinforcement. The second indicator is prospective behavior with 12 items that comprise of communication, problem-solving, and self-management. The third indicator is ICT skills, with eight items that encompass comfort and skills in ICT usage. Further, the students were asked to choose the 1-4 Likert scale for each statement in that questionnaire. Score 1 represents extreme disagreement; score 2 means argument; score 3 means agreement, and score 4 means extreme agreement. The validity of this instrument has been tested through a product-moment correlation, while its reliability has been tested using Cronbach's Alpha. The results of the instrument test show that its items are valid and reliable as presented in Table 1. The data collection process was carried out using Google Form application in April 2020. This method was chosen since it is more efficient to collect data during the implementation of learning from a home policy from the Indonesia Ministry of Education due to the rapid spread of the Corona 19 virus in Indonesia. This research used a descriptive analysis method to reveal the score, average, standard deviation, the maximum and minimum score for each indicator. Further, the level of students' motivation, prospective behavior, and ICT skills are categorized based on score, as presented in Table 2.  [48] In addition, one-way ANOVA analysis was used to see the effect of different gender toward the score in each indicator. Before the one-way ANOVA analysis, a normality test using the One-Sample Kolmogorov-Smirnov Test and homogeneity test using Levene's Test had been conducted. The statistic analysis test was assisted SPSS Statistics 22 program.
The hypothesis tests for indicator motivation, prospective behavior, and ICT skills are: i) H0: no difference in students' motivation, prospective behavior, and ICT skills in PBHL, seen from the gender type; and ii) H1: there is a difference in students' motivation, prospective behavior, and ICT skills in PBHL, seen from the gender type. Meanwhile, the criteria for decision making are if the significance value ≥0.05, then H0 is accepted. If the significance value <0.05, then H0 is rejected.

Students' preparedness in PBHL
The motivation, prospective behavior, and ICT skill score of social science education students in PBHL are shown in Table 3. The table shows that the highest and lowest average score of social science students on motivation indicators in PBHL is obtained by perception and self-efficacy, respectively. Generally, social science education students' motivation is categorized high, in all sub-indicators. In addition, the highest and lowest average score of social science students' on prospective behavior indicators in PBHL is gained by communication and self-management, respectively. The level of prospective behavior of social science education students in PBHL is classified as high on sub-indicator communication and problemsolving; meanwhile, sub-indicator self-management is categorized as moderate. Besides, the highest and lowest average score of social science students' on ICT skills indicator in PBHL is attained by skills on using ICT and comfort in using ICT, respectively. The ICT skills level of social science education students in PBHL is grouped as very high in sub-indicator skill and low in sub-indicator comfort in using ICT. According to results on the analysis of each indicator, the social science education students' preparedness scores in PBHL are presented in Table 4.  Table 4 reveals that the preparedness of social science education students in PBHL is classified as high on all indicators. The comparison of the average score on each indicator is illustrated in Figure 1. The figure presents that the highest average score on social science education students' preparedness in PBHL is in motivation (80.62), while the lowest average score is in ICT skills (77.76). The level of social science education students' preparedness in PBHL is classified as high. This is concluded from the category of each readiness indicator based on assessment criteria used in UIN Maulana Malik Ibrahim Malang are categorized as B+ category. Thus, the PBHL model is expected to be implemented in social science education classes with no obstructions.
Two essential elements support the success of PBHL implementation, which is students' classroom learning experience and heir ICT usage [31]. Classroom learning experience comes from various models applied by lecturers in the learning process. Besides, students' involvement in using ICT is one of the manifestations of the millennial generation who generally has been familiar with computers and the internet. Therefore, social science students, as the millennial generation, have commonly adapted to ICT usage. All of these factors simultaneously improve their mental function, so students' preparedness is established.
The results of the study conducted by Horzum et al. [49] discover that ICT skills effectively predict academic motivation in accelerating online learning. Recently, students frequently look for online references to finish their task, then send it through email [50]. This activity involves ICT skills, including necessary skills in operating technology, access easiness, as well as interacting using technology [46]. Students possess excellent skills in technology-based learning and have great technical skills required in technology operation [51]. Additionally, Xiong et al. [47] state that the online learning ability subsists of two aspects, ICT skills and the comfort in attending online learning. These two aspects can be sharpened through frequent usage of the internet to gain a positive impact on the performance [43].
In addition, students' readiness in PBHL is one of the critical aspects to be considered. The students are in the high mental function when they are ready to follow the classroom learning and obtain new concepts [52]. Later, students preparedness also generate bravery to do and create something new, especially when they get support from the institution and cultural changes [53], [54]. Institutional supports and cultural differences are significant in deciding students' readiness in the learning process. Further, to support the exceptional PBHL implementation, the pedagogy students' preparedness and accessibility should be a balance [55].

Effect of different gender on students' motivation, prospective behaviour, and ICT skills in PBHL
The results of the normality test on motivation, prospective behavior, and ICT skills are shown in Table 5. Based on the table, the results of data normality test are: i) The score of indicator motivation is sig.=0.434>α=0.05, meaning that the motivation data has a normal distribution; ii) The score of the prospective behavior indicator is sig.=0.272>α=0.05, signifying that the prospective behavior data has a normal distribution; ii) The score of the ICT skills indicator is sig.=0.092>α=0.05, implying that the ICT skills data has a normal distribution. Results of the data homogeneity test on motivation, prospective behavior, and ICT skill are presented in Table 6. According to the data, the results of homogeneity test are: i) The score of motivation indicator is sig.=0.041<α=0.05, suggesting that the motivation data has no homogenous variation; ii) The score of the prospective behavior indicator is sig.=0.708>α=0.05, implying that prospective behavior has homogenous variation; iii) The score of the ICT skills indicator is sig.=0.776>α=0.05, signifying that the ICT skills data has homogenous variation. The data on motivation, prospective behavior, and ICT skills were analyzed using one-way ANOVA. The summary of the results of one-way ANOVA is presented in  According to the analysis, the conclusion that can be made is gender difference brings no significant effect on social science education students' motivation, prospective behavior, and ICT skills in PBHL. Both male and female students demonstrate high preparedness in PBHL. There is no students' different preparedness level in PBHL, reviewed from gender type. According to the results of one-way ANOVA analysis, different gender type carries no significant effect on social science education students' readiness to attend PBHL. The preparedness of female and male students relies on their motivation, prospective behavior, and ICT skills.
Students' motivation on blended face-to-face and online learning is not affected by gender type, but they are affected by their behavior on technology usage, beliefs in technology usage, and decreased technology anxiety [56]. Motivation contributes to students' knowledge management and self-management in an online learning context [57]. Besides, motivation is also presumed to affect students' performance, primarily on the small-group discussion in PBL [58]. Motivation becomes the factor that predicts students' preparedness in learning [59]. Other than that, motivation also contributes to online learning success and satisfaction in universities [60]. It also turns into a factor that determines students' persistence and improves students' behavior in the classroom [61].
The results of this research reveal that gender type brings no significant effect on prospective behavior. The prospective behavior that supports students' preparedness in PBHL covers the habits in using ICT and collaboration. The practices of using ICT is closely related to the internet-based learning process. This practices that transform into students' pattern in the information era has the potential to support readiness in PBHL [50]. Besides, the habits of using the internet contribute to the development of online communication and collaboration outside the class [62]. Further, the collaboration practices are also associated with the social skill to attain collected purposes in group discussion. The collaboration culture gained from classroom discussion learning also contributes to students' preparedness in PBHL class [63]. PBL trains students to solve problems in a group, be responsible for it, as well as communication and collaboration during the process of solving the problem.

CONCLUSION
The results of this research show that students' ICT skills in PBHL learning carry no differences, seen from the gender type. The expertise in using ICT is a significant factor of preparedness in online learning, as proven by the results of this research that classified as very high. Generally, social science education students' preparedness in PBHL is classified as high. At the same time, the gender difference brings no significant effect on social science students' readiness in PBHL. Based on the results of this research, some recommendations are concluded. First, the implementation of PBHL does not require a consideration of different gender types since it has been proven to bring no significant effect on students' readiness. Second, the university has to facilitate easy internet access, such as by accelerating the bandwidth, internet connection, and promote other policies that support PBHL.

BIOGRAPHIES OF AUTHORS
Saiful Amin is a doctor, lecturer, and researcher at Departement of Social Science Education, Faculty of Tarbiyah and Teacher Training, Universitas Islam Negeri Maulana Malik Ibrahim Malang, Indonesia. He has successfully completed her bachelor degree, master of education degree, and PhD in Geography Education from Universitas Negeri Malang, Indonesia. Field of expertises are in geography learning, education & teacher training, social science education, and social sensitivity. He can be contacted at email: amin.geo87@pips.uin-malang.ac.id.

Sumarmi
is a professor, lecturer, and researcher at Department of Geography Education, Faculty of Social Sciences, Universitas Negeri Malang, Indonesia. She has successfully completed her bachelor degree in Geography Education and Master of Education degree from Universitas Negeri Malang, Indonesia. She obtained PhD in Environmental Science from Universitas Brawijaya Malang, Indonesia. Field of expertises are in environmental geography, geography learning, and environmental education based on local wisdom. She can be contacted at email: sumarmi.fis@um.ac.id.

Ravinesh Rohit Prasad
is an assistant professor at the Department of Social Sciences, School of Arts and Humanities, Fiji National University, Fiji. He has successfully completed his Diploma in Education from the Fiji College of Advanced Education (now Fiji National University) and a Bachelor of Arts Degree from the University of the South Pacific, Suva, Fiji. He obtained his Master of Arts degree in Geography Education and PhD in Geography Education from Universitas Negeri Malang, Indonesia. His research interests are climate change perception, geography and social education. He can be contacted at email: ravinesh.prasad1@fnu.ac.fj.