Time Series Prediction of Viable Embryo and Automatic Grading in IVF using Deep Learning

Background: The process of In Vitro Fertilization (IVF) involves collecting multiple samples of mature eggs that are fertilized with sperms in the IVF laboratory. They are eventually graded, and the most viable embryo out of all the samples is selected for transfer in the mother’s womb for a healthy pregnancy. Currently, the process of grading and selecting the healthiest embryo is performed by visual morphology, and manual records are maintained by embryologists. Objectives: Maintaining manual records makes the process very tedious, time-consuming, and error-prone. The absence of a universal grading leads to high subjectivity and low success rate of pregnancy. To improve the chances of pregnancy, multiple embryos are transferred in the womb elevating the risk of multiple pregnancies. In this paper, we propose a deep learning-based method to perform the automatic grading of the embryos using time series prediction with Long Short Term Memory (LSTM) and Convolutional Neural Network (CNN). Methods: CNN extracts the features of the images of embryos, and a sequence of such features is fed to LSTM for time series prediction, which gives the final grade. Results: Our model gave an ideal accuracy of 100% on training and validation. A comparison of obtained results is made with those obtained from a GRU model as well as other pre-trained models. Conclusion: The automated process is robust and eliminates subjectivity. The days-long hard work can now be replaced with our model, which gives the grading within 8 seconds with a GPU.

Clustering Algorithm to Measure Student Assessment Accuracy: A Double Study

Self-assessment is one of the strategies used in active teaching to engage students in the entire learning process, in the form of self-regulated academic learning. This study aims to assess the possibility of including self-evaluation in the student’s final grade, not just as a self-assessment that allows students to predict the grade obtained but also as something to weigh on the final grade. Two different curricular units are used, both from the first year of graduation, one from the international relations course (N = 29) and the other from the computer science and computer engineering courses (N = 50). Students were asked to self-assess at each of the two evaluation moments of each unit, after submitting their work/test and after knowing the correct answers. This study uses statistical analysis as well as a clustering algorithm (K-means) on the data to try to gain deeper knowledge and visual insights into the data and the patterns among them. It was verified that there are no differences between the obtained grade and the thought grade by gender and age variables, but a direct correlation was found between the thought grade averages and the grade level. The difference is less accentuated at the second moment of evaluation—which suggests that an improvement in the self-assessment skill occurs from the first to the second evaluation moment.

Seeing differently from others: the impact of relationship conflict asymmetry and realization on team performance

Purpose Past research on team conflict has often conceptualized it as a collective phenomenon whereby members of the same team perceive similar levels of conflict. However, similarity in perspectives can more often be the exception than the norm. As such, the purpose of this paper is to examine the effects of relationship conflict (RC) asymmetry on information elaboration and team performance. Additionally, I introduce a new construct: perception of team RC asymmetry and propose that it strengthens the positive effects of RC asymmetry. Design/methodology/approach A total of 181 MBA students comprising 52 teams participated in the research. Students worked together for the duration of the semester to complete a team project that comprised 45% of their final grade. Surveys were administered at three points in time with performance measured at the end and other focal variables measured at the midpoint. Regression analyses and the PROCESS macro were used to examine a first stage moderated mediation model. Findings Results showed that RC asymmetry increased elaboration, which, in turn, improved team performance. The link between RC asymmetry and elaboration was moderated by the perception of team RC asymmetry. Originality/value The present research shows that to have a fuller understanding of RC one must consider the level of dispersion experienced by team members. Taking this approach has uncovered a way in which RC can actually benefit teams instead of lead to destructive outcomes.

Text Mining Data from Students to Reveal Meaningful Information for Educators

Academic institutions adopt different advising tools for various objectives. Past research used both numeric and text data to predict students’ performance. Moreover, numerous research projects have been conducted to find different learning strategies and profiles of students. Those strategies of learning together with academic profiles assisted in the advising process. This research proposes an approach to supplement these activities by text mining students’ essays to better understand different students’ profiles across different courses (subjects). Text analysis was performed on 99 essays written by undergraduate students in three different courses. The essays and terms were projected in a 20-dimensional vector space. The 20 dimensions were used as independent variables in a regression analysis to predict a student’s final grade in a course. Further analyses were performed on the dimensions found statistically significant. This study is a preliminary analysis to demonstrate a novel approach of extracting meaningful information by text mining essays written by students to develop an advising tool that can be used by educators.

Converting cumulative grade point average to an equivalent percentage value based on a fuzzy logic

The graduates who have finished their study program will be given a merit award and their award certificates will be graded in accordance with the degree of their academic accomplishment. The awards are generally offered using two methods; one is by the cumulative grade point average (CGPA) and the other is by the average percentage of all marks for the students. The problem is when assigning a course final grade; each student's final percentage is translated to a letter, allowing the discrepancy within the same letter grade range in the final ranking. If two students have the same final score, that means equal results. However, this equality can be false if one student hits a percentage of the highest grade, while the second student earns a percentage of the lowest grade of the same letter grade. This paper introduced a new equation that transforms between the awarded cumulative grade point average and the awarded percentage ranking based on fuzzy system. The proposed approach was tested using three actual benchmarks collected from three different colleges in Beni-Suef university. The obtained results reflects the effect of the fuzzy logic in helping converting form CGPA measures to percentage measure in educational systems.

The two roads of passionate goal pursuit: links with appraisal, coping, and academic achievement

Background and Objectives: In this research, we testing the role of cognitive appraisals in explaining why harmonious and obsessive passion dimensions are related to distinct forms of coping, and explored if performance was impacted by these appraisal and coping processes.Design: Undergraduate students (N = 489) participated in a longitudinal study and completed three surveys throughout the course of an academic year.Methods: Participants completed assessments of both passion dimensions (Time 1), reported how they were appraising and coping with the mid-year exam period (Time 2), and provided consent to obtain their final grade in Introductory Psychology (Time 3). The hypothesised model was tested using structural equation modeling.Results: Harmonious and obsessive passion dimensions were linked with approach and avoidant coping responses, respectively. Cognitive appraisals, particularly appraisals of challenge and uncontrollability, played an indirect role in these relationships. In addition, both appraisals and coping responses had an indirect effect in the relationship between passion dimensions and final grade. Conclusions: These results identify cognitive appraisal as a reason why passion dimensions are linked with distinct coping tendencies, and demonstrate the role appraisal and coping processes in the journey toward passionate goal attainment.

Monitoring and evaluation procedure with LMS Moodle

The purpose of the article is to develop recommendations for results processing in Moodle electronic system. Methodology: the authors presented formulas for calculating the reliability of the tests used to verify students' training, the description of what is required for monitoring, the actions of the teacher to perform a quality assessment system. The process of calculating the final grade for the course is presented, which will provide the necessary conditions for conducting student knowledge control. Results: in the process of study, it was concluded that modern methods of processing the data used during the control measures in higher education institutions within the framework of the Moodle system contribute to improving the graduates training.

The Effect of Specifications Grading on Students’ Learning and Attitudes in an Undergraduate-Level Cell Biology Course

Specifications (specs) grading is a grading system in which mastery of specific educational outcomes is the basis for the final grade a student earns in the course. Implementation of the types of assessments used for specs grading has shown to be beneficial for student learning and motivation compared to traditional grading systems. We designed a specs grading strategy in an undergraduate Cell Biology course, creating 20 individual learning outcomes (LOs).

Family Medicine Clerkship Assessment Analysis: Application and Implications

Introduction: Clerkship assessment structures should consist of a systematic process that includes information from exam and assignment data to legitimize student grades and achievement. Analyzing student performance across assessments, rather than on a single assignment, provides a more accurate picture to identify academically at-risk students. This paper presents the development and implications of a structured approach to assessment analysis for the Family Medicine Clerkship at Florida International University Herbert Wertheim College of Medicine. Methods: The assessment analysis included a table presenting the distribution of all assessment performance results for 166 clerkship students from April 2018 to June 2019. A correlation table showed linear relationships between performance on all graded activities. We conducted a Pearson analysis (r), coefficient of determination (r2), multiple regression analysis, and reliability of performance analysis. Results: Performance on one assessment—the core skills quiz—yielded a statistically significant correlation (r=.409, r2= .16, P<.001) with the final clerkship grade. The reliability of performance analyses showed low performers (<-1.7 SD), had both a low mean quiz score (59.6) and final grade (83). Top performers (>-1.7 SD) had both a high mean quiz score (88.5) and final grade (99.6). This was confirmed by multiple regression analysis. Conclusion: The assessment analysis revealed a strong linear relationship between the core skills quiz and final grade; this relationship did not exist for other assignments. In response to the assessment analysis, the clerkship adjusted the grading weight of its assignments to reflect their utility in differentiating academic performance and implemented faculty development regarding grading for multiple assignments.