Enhancing Graduate Students’ Reflection in E-Portfolios Using the TPACK Framework

When electronic portfolios (e-portfolios) are employed as summative assessments for degree granting programs, it is imperative that graduate students demonstrate their knowledge in the field to showcase learning growth and achievement of the program learning outcomes. This study examined the extent master\u27s degree students in the field of educational technology demonstrated their technological pedagogical content knowledge (TPACK) related elements in their e-portfolio reflection, when they were guided by TPACK framework grounded instruction. Using content analysis technique and open-ended survey responses, the findings show that graduate students were able to demonstrate their interconnected technological pedagogical knowledge in their reflection to justify their competencies. In addition, graduate students had positive reactions to the opportunity to reflect through writing the reflection paper. This study contributes to the e-portfolio literature by signifying the importance of providing a discipline-specific framework to guide students’ reflection of learning. The TPACK grounded instruction helped graduate students stay focused on their reflection. This study also contributes to the TPACK literature by demonstrating the extent to which graduate students presented their integrated knowledge of TPACK at the end of a program driven to developing students’ technology integration expertise

The relationship between velocity utilization rate and pole vault performance

In the pole vault event, the velocity of approach is a highly vital factor. As velocity of approach improvements highly impact performance improvements. This study analysed the relationships between sprint running’s speed (SR), pole running (PR, without jump), and the pole vault approach (PVA, with real jump). Analysed too were the relationships between both the approach and performance’s respective running distance, velocity, and velocity utilization rates. Methods: Ten male pole vaulters were recruited. Measured was each 5-meter segment’s average velocity of his respective SR, PR, and PVA, along with the distance to maximum velocity. Results: The maximum average velocity of the PR’s 5m segments altogether was significantly positively correlated with pole vault (PV) performance; The maximum average velocity of the PR’s 5m segments altogether was significantly positively correlated with the last 5m PVA average velocity; The PVA velocity’s utilization rate was significantly negatively correlated with the difference between the distance to the PR’s maximum velocity and the PVA’s distance. Conclusion: The PR segment’s maximum speed capability can evaluate both a pole vaulter’s potential and pole vault-specific abilities. This study’s recruited pole vaulters’ respective approach distances were generally insufficient that resulted in a lower velocity utilization rate. Suggested is that in training, the pole vaulter could first find the distance required to reach the highest velocity upon starting from the PR test. Thus, this subsequently known distance could be applied in tandem with the pole vault’s approach to both improve the PVA’s utilization rate and reach the individual highest speed level

A Geometrically Constrained Point Matching based on View-invariant Cross-ratios, and Homography

In computer vision, finding point correspondence among images plays an important role in many applications, such as image stitching, image retrieval, visual localization, etc. Most of the research worksfocus on the matching of local feature before a sampling method is employed, such as RANSAC, to verify initial matching results via repeated fitting of certain global transformation among the images. However, incorrect matches may still exist, while careful examination of such problems is often skipped. Accordingly, a geometrically constrained algorithm is proposed in this work to verify the correctness of initially matched SIFT keypoints based on view-invariant cross-ratios (CRs). By randomly forming pentagons from these keypoints and matching their shape and location among images with CRs, robust planar region estimation can be achieved efficiently for the above verification, while correct and incorrect matches of keypoints can be examined easily with respect to those shape and location matched pentagons. Experimental results show that satisfactory results can be obtained for various scenes with single as well as multiple planar regions

The efficacy of stereotactic body radiation therapy on huge hepatocellular carcinoma unsuitable for other local modalities

BACKGROUND AND AIM: To evaluate the safety and efficacy of Cyberknife stereotactic body radiation therapy (SBRT) and its effect on survival in patients with unresectable huge hepatocellular carcinoma (HCC) unsuitable of other standard treatment option. METHODS: Between 2009 and 2011, 22 patients with unresectable huge HCC (≧10 cm) were treated with SBRT. dose ranged from 26 Gy to 40 Gy in five fractions. Overall survival (OS) and disease-progression free survival (DPFS) were determined by Kaplan-Meier analysis. Tumor response and toxicities were also assessed. RESULTS: After a median follow-up of 11.5 month (range 2–46 months). The objective response rate was achieved in 86.3% (complete response (CR): 22.7% and partial response (PR): 63.6%). The 1-yr. local control rate was 55.56%. The 1-year OS was 50% and median survival was 11 months (range 2–46 months). In univariate analysis, Child-Pugh stage (p = 0.0056) and SBRT dose (p = 0.0017) were significant factors for survival. However, in multivariate analysis, SBRT dose (p = 0.0072) was the most significant factor, while Child-Pugh stage of borderline significance. (p = 0.0514). Acute toxicities were mild and well tolerated. CONCLUSION: This study showed that SBRT can be delivered safely to huge HCC and achieved a substantial tumor regression and survival. The results suggest this technique should be considered a salvage treatment. However, local and regional recurrence remain the major cause of failure. Further studies of combination of SBRT and other treatment modalities may be reasonable

Elementary School Student Development of STEM Attitudes and Perceived Learning in a STEM Integrated Robotics Curriculum

Robotics has been advocated as an emerging approach to engaging K-12 students in learning science, technology, engineering, and mathematics (STEM). This study examined the impacts of a project-based STEM integrated robotics curriculum on elementary school students’ attitudes toward STEM and perceived learning in an afterschool setting. Three elementary school teachers and 18 fourth to sixth graders participated in an eight-week-long program. Quantitative and qualitative data were collected and analyzed, and showed students’ attitudes toward math improved significantly at the end of the robotics curriculum. Three specific areas of learning were identified, including STEM content learning and connection, engagement and perseverance, and development and challenge in teamwork. The findings also identified the opportunities and challenges in designing a STEM integrated robotics afterschool curriculum for upper elementary school students. Implications for future research studies and curriculum design are discussed

Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning

An intelligent robot agent based on domain ontology, machine learning mechanism, and Fuzzy Markup Language (FML) for students and robot co-learning is presented in this paper. The machine-human co-learning model is established to help various students learn the mathematical concepts based on their learning ability and performance. Meanwhile, the robot acts as a teacher's assistant to co-learn with children in the class. The FML-based knowledge base and rule base are embedded in the robot so that the teachers can get feedback from the robot on whether students make progress or not. Next, we inferred students' learning performance based on learning content's difficulty and students' ability, concentration level, as well as teamwork sprit in the class. Experimental results show that learning with the robot is helpful for disadvantaged and below-basic children. Moreover, the accuracy of the intelligent FML-based agent for student learning is increased after machine learning mechanism.Comment: This paper is submitted to IEEE WCCI 2018 Conference for revie