The purpose of this study is to develop a standardized measurement tool that can be used to determine the participation styles of individuals participating in online instructional discussions. The scale consists of two dimensions called 'Why' and 'How.' The Why dimension comprises the main motivators of the participants' participation in online instructional environments, whereas the How dimension comprises items expressing participation behaviors or forms. Two separate datasets were used for exploratory factor analysis (450 participants) and confirmatory factor analysis (693 participants), and the scale was applied to both undergraduate and graduate students. The scale consisted of eight factors, with four in the Why dimension and four in the How dimension. The results of confirmatory factor analysis showed that the scale was able to identify four different patterns of participation. Expressed as participation styles, these patterns are To Socialize/Connective, To Get Information/Analytical, To Discuss/Innovative, and To Fulfill Requirements/Practical. According to these results, the Participation Style Scale for Online Instructional Discussions was assumed to be a valid and a reliable measurement tool for determining the participation styles of participants of online instructional discussions. These four styles are thought to contribute to the instructors, the researchers, and the learners who want to benefit from effective learning in online environments. Instructors and researchers can determine learners' participation styles before organizing discussion environments, and learners who think and gain awareness about their own participation styles can manage their discussion and learning processes more effectively.
The purpose of this study was to determine the opinions of teacher candidates on programming education. In this context, the opinions of the participants about the programming languages they had learned (C/C#, Arduino, Scratch), which methods they prefer to learn and the problems they had experienced in the process have been tried to be determined. The participants included in this study were composed of 25 sophomore teacher candidates who were studying at the department of Computer Education and Instructional Technologies. 16 participants were female and nine were male. Descriptive method is used in study. The opinions of teacher candidates were collected via questionnaire. According to the results, teacher candidates have a positive view of all platforms. However, it has been determined that the opinions about C and Arduino platforms differ according to gender that female teacher candidates find these languages more difficult. Teacher candidates want to learn the programing in guidance of the instructor. When the problems faced by teacher candidates in learning programming are examined, it is seen that the problems are more in Arduino project group.
In this study, the effect of algorithm education on teacher candidates’ computational thinking skills and computer programming self-efficacy perceptions were examined. In the study, one group pretest posttest experimental design was employed. The participants consisted of 24 (14 males and 10 females) teacher candidates, majoring in Computer Education and Instructional Technology (CEIT). In order to determine the teacher candidates’ computer programming self-efficacy perceptions, the Computer Programming Self-Efficacy Scale was used, whereas Computational Thinking Skills Scale was used to determine their computational thinking skills. The Wilcoxon Signed-Rank Test was used to analyze the differences between pretest and posttest scores of students' computer programming self-efficacy perceptions and computational thinking skills. Throughout the practices, 10 different algorithmic problems were presented to the students each week, and they were asked to solve these problems using flow chart. For 13 weeks, 130 different algorithmic problems were solved. Algorithm education positively and significantly increased students' simple programming tasks, complex programming tasks and programming self-efficacy perceptions. On the other hand, algorithm education had a positive and significant effect only on students’ algorithmic thinking sub-dimension but did not have any effect on other sub-dimensions and computational thinking skills in general.
The three essential elements of an effective instructional environment are the students, the curriculum and the teacher. The teacher, on the other hand is the glue that combines these items. To train qualified teachers, it is important to use methods that employ theory and practice together in teacher education. In order for microteaching, one of these methods, to be more effective, supporting it with online environments such as social networks may be beneficial. In this respect, this study aims to find out the effects of Social Network-Supported Microteaching (SNSM) on self-efficacy and teaching skills of pre-service teachers. The study was conducted using mixed research model. The participants of the research are 17 pre-service teachers from the Department of Computer Education and Instructional Technology. Teacher Self-Efficacy Scale (TSES) and Open-Ended Interview Questionnaire (OEIQ) developed by researchers were used for data collection. The SNSM process took place in two stages. Pre-service teachers were asked to respond to Teacher Self-Efficacy Scale prior to SNSM, at the end of the first stage and subsequent to the SNSM. Following SNSM, through the open-ended interview questionnaire, opinions of the pre-service teachers were received and the data on the effect of SNSM on teaching skills were collected. Following the collection of data, quantitative and qualitative data were analysed. Consequently, quantitative results indicated that SNSM increased teacher self-efficacy levels in terms of student engagement, classroom management and teaching methods. Qualitative data was in support of quantitative data, and pre-service teachers have expressly stated that SNSM has improved their teaching skills.Keywords: Microteaching; social network-supported learning; teacher education.
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