This research investigated the effects of different learning modes (traditional, online, distributed) on students' performance, confidence, and motivation in an introductory computer science course. Students were randomly assigned to one of the three learning modes. Their pre-existing computer knowledge was assessed with a pre-test, and their performance, confidence, and motivation were measured with a post-test and questionnaire at the end of the semester. Data analysis using ANOVA would determine if any learning mode led to better outcomes.

1. Title of Research To investigate student’s learning attitudes and performance of a computer course with different modes of learning (i.e. traditional classroom-based, online learning, distributed learning) Research Questions: Will students perform better on a computer course if they are taking distributed learning mode ? Will students have more confidence in learning a computer course if they are taking distributed learning mode? Participants: University year one students who are taking COMP1 01 (computer science core course )

2. Important to teaching and learning Find a mode of learning which are most benefit to student (i.e. high confidence, high motivation and good academic performance) to learn a computer course We may offer more courses on this mode of learning We may consider to extend to other courses if further investigation is positive

3. Data Collection and Analysis At the beginning of semester, student may a simple test about the knowledge of subject (pre-test) Mode of learning of the computer course will be assigned to s tudents and they could not change it after starting the course Three groups of student are near the same computer knowledge At the beginning (pre-test) and at the end of semester (post-test) Student self assessment of confidence and motivation by questionnaire Academic performance could be obtained from quiz or examination at the end of semester (post-test) Dat a Analysis tools ANOVA