language Scratch (2009)26 as a tool in order to seedCT and CS concepts in both institute participants and pre-service teachers. We also describe aself-efficacy instrument used to measure STEM experiences, 21st century learning skills, andCT. The importance of this research is to discover whether or not past STEM activities andexperiences will transfer to student self-efficacy in CT, as well as develop a method fordelivering and measuring CT skills in the K-12 environment.BackgroundVisual based programming tools have become largely popular due to their ease of use forbeginner programmers in not only K-12, but also higher education. These block-basedprogramming languages have made their way into many STEM outreach programs in order totrain both
persistence as a manifestation of motivation,while Graham et al [6] view motivation as a driver of student engagement. Self-efficacy orconfidence is one among several constructs underlying motivation. Programs that have beensuccessful in improving the persistence of college students in STEM deploy threeinterventions, which include: 1) early research experiences, 2) active learning, and 3)membership in STEM learning communities.3. Literature ReviewStrategies to improve knowledge retention and student interest in Computer ScienceProblem-based Learning (PBL) is an instructional model that may prove a good fit forcomputer science education due to the problem-solving basis that is also a quality shared withthe nature of many STEM careers. Problem solving
-theft anxiety level in college students. This study performed several analyses ona developed questionnaire to ensure validity and reliability. After examining all proposedhypotheses, it was found that electronic devices self-efficacy and electronic devices usage havesignificant impact on identity-theft anxiety level of the students. The data also support arelationship between information security awareness of the students and their identity-theftanxiety level. This research also showed that gender, employment status, race, and age havemoderating effects on all hypotheses. The outcome of this study indicated that moreinformation should be provided to students regarding how to take proactive measures inusing their electronic devices in order to
changes in studentinterest and self-efficacy as they relate to cybersecurity.Measuring change in student interest gives us an indication of how well a given course ismotivating students to pursue further knowledge or work in this sub-field. 22 Building long-termstudent interest is vital within a new, fast-changing, field such as cybersecurity. Self-efficacy isdefined as “...a person’s belief in his or her capability to perform a task,” 8 Measuring studentself-efficacy is important because it has been linked with outcomes such as persistence on task,academic success and long-term career success. 4,19 Studies have shown that students with higherself-efficacy in fields such as mathematics are more willing to discard faulty strategies and reworkmore
exploration as a theme, and the other used micro controllers as thefoundation for activities. The goals of this research are as follows: 1. Develop effectivecurricula for improving student self-efficacy in CT, 2. Develop a reliable and effective wayof measuring student self-efficacy in CT, and 3. Enforce the notion that CT is not problemsolving (PS), but a component of cognition.Background and Related Work“Computational thinking involves solving problems, designing systems, and understandinghuman behavior, by drawing on the concepts fundamental to computer science”26. However,computational thinking (CT) is not intended to be equated to computer science; rather theessence of CT comes from thinking like a computer scientist when faced with problems
studentcharacteristics that have been shown to lead towards success in the classroom and influencestudent career selection. These characteristics include self-efficacy in relation to cybersecurity,student interest in further coursework, and research or jobs that involve cybersecurityconcepts 3,12 . By interviewing students enrolled in a cybersecurity course, at multiple pointsduring the semester, we are able to identify student interests and perceptions of cybersecurity anddocument changes in student self-efficacy and interest that occur as the semester progresses.Furthermore, we identify pedagogical practices which students found most useful through thissemester-long investigation. The results from this study will be used to construct a Likert-typescale survey
teams of four and complete in-class homework and projectchallenges with their team. Teams are assigned using a survey (discussed later) in order tobalance out multiple individual characteristics such as gender mix and self-reported efficacy andprior learning. The exact ‘formula’ by which the team assignments are made varies slightly inyear, but generally uses the same categories of data later discussed in Table 1. The methodologyfor forming team attempts to pick a ‘ringer’ for each team, based on self-reported self-efficacy inprogramming. The ringer is chosen based on the reported programming skills, but is balancedacross the demographic factors mentioned earlier as well as ensuring a balance of experienced,somewhat experienced and novice
research instrument: self-efficacy, research skills, and scientificleadership. The sections below describe survey questions from each of these survey sections. Atotal of 17 questions are provided: 5 from General Self-Efficacy, one (1) from Research Skillsand Knowledge, and 11 from Scientific Leadership.General Self-Efficacy Feedback from students on general self-efficacy addresses student confidence in theirability to perform each of the activities listed in Table 5. Students select the rating that bestdescribe their degree of confidence by using the following scale: Strongly Agree (5), SomewhatAgree (4), Neutral (3), Somewhat Disagree (2), and Strongly Disagree (1).Table 5. General Self-Efficacy Student Survey 2015 Post Questions
cooperation scaffolding might hinder students’ cooperation inlearning. The impacts of scaffolding on students' learning dispositions measured by MSLQ 23 wereexamined by comparing results between the post-test and the pre-test in terms of size effect, asshown in Table 10. According to the comparison, Group B enjoyed the increase in self-efficacy, intrinsic value, cognitive strategy use and self-regulation, but suffered intensified testanxiety. Group C, similar to Group D, experienced increase in self-efficacy and reduced testanxiety, but failed to develop in intrinsic value cognitive strategy use and self-regulation.However, Group D enjoyed the boldest increase in self-efficacy and largest decrease in testanxiety, but they suffered the largest
teaching at too fast a pace. In addition, many students felt that theylacked suitable preparation through prior experience, particularly in programming skills anddatabase concepts. 2,3,5,6A few studies found that the students’ ability to integrate into the academic and socialenvironment of the university played an important role in retention.3 The most important factorin this integration was building a peer group support system through peer interaction in theclassroom.5,7,8 In addition, student-faculty relationships were also very important to academicintegration. Students had to feel comfortable interacting with faculty members.2,8 However,Weng et al. found that self-efficacy, or the ability to persist in the face of obstacles, was moreimportant
4: Average number ofmessages per forum, Total number of messages per forum and Number of students participatingin each forum. As education researchers, our aim is to correlate these numbers to grades, andconstructs such as motivation, and self-efficacy, and to study if participation affects learningoutcomes. Each graph shows bars that correspond to numbers of initial posts, responses and totalposts. The instructor suggested that longer threads might mean more student confusion, andgenerally speaking, more activity means more student problems. He commented that he didn’tneed to see all the forums, only the one theoretical (lecture) forum and the four project(assignment) forums were important. The assignments were mutually exclusive, so he
, whereas social influence plays the role of a subjective normand is a direct determinant of behavioural intention. Marchewka, Liu and Kostiwa 8tested the UTAUT model to understand students’ perceptions about using Blackboardand showed that effort expectancy and social influence were significant determinants ofstudents’ behavioural intention. Chiu and Wang 9 indicated that performance expectancy,effort expectancy, computer self-efficacy, attainment value, utility value and intrinsicvalue are significant predictors of individuals’ intentions to continue using Web-basedlearning, while anxiety can have a significant negative effect.Because of its novelty in the field of user acceptance research, the UTAUT model waschosen as a theoretical framework in
processes with interactive assessment activities thatprovides immediate feedback to students. From a learning perspective, they are intended to movestudents from a passive stance in a lecture-type classroom setting to an active position of con-structing learning and tracking their own comprehension through immediate feedback receivedfrom the exercises.The theory of change driving the design and implementation of these tutorials is to encouragestudents’ engagement with the content materials and involve them in the loop of assessment asactive participants in such a way that they as well as their instructors know that they are learning.According to Bandura’s9 cognitive theory of self efficacy, instruction that allows students tocheck their own