Assessment and feedback mechanisms are essential components towards effective teaching in higher education and are continuously monitored. The annual student satisfaction survey in UK higher education collects students’ perception on those dimensions and issues results to assist institutions identify their weaknesses and amend their strategies and improve their teaching effectiveness. This study explores assessment and feedback as predictors for overall student satisfaction. It focuses on business schools mainly and uses the officially published dataset. Following a regression analysis approach, it can be concluded that there is evidence to support the claim that assessment and marking can be used as predictors for overall student satisfaction in this subdomain. The significance of the study lies in the fact that universities consider assessment and feedback as of key importance for improving student experience. It is thus critical for the institutions to gain a better understanding on whether those factors can be safely used as predictors of overall student satisfaction, something that is related to university ranking tables. Results in the study, demonstrate some important aspects of this and indicate that improved quality in marking and feedback can have a positive effect in student satisfaction. A more comprehensive study can unfold additional dimensions of the survey and shed light on how students perceive marking, assessment and feedback in higher education in general.

In online education through web conference tools, teachers cannot grasp students' states by watching their behaviors like in an offline classroom. Each student also cannot be affected by others' good behavior. This paper proposes a prediction method of the student effort through acceleration sensors and a heart rate sensor worn on a student's body, and a local camera. The effort is expressed by the levels of concentration, excitation, and bodily action. A Random Forest regression model is used to predict each level from the sensor and camera data. Exhibiting the prediction result brings visibility of student states like offline. We verified the effectiveness of the prediction model through an experiment. We built the Random Forest regression prediction models from the sensors, camera, and student effort data obtained by actual lectures. In the case of building one prediction model for one lecture/one subject, the average R2 values were 0.953, 0.925, and 0.930 in the concentration, excitation, and bodily action, respectively. The R2 was -0.835 when one prediction model trained by one lecture's data is applied for another lecture's prediction. That was 0.285 when one model by 4 subjects' data is applied for prediction for the rest 1 subject. It means that the prediction model has high accuracy but is dependent on individual persons and lectures, which forces a burden to individual student to collect initial training data for individual lecture to build a prediction model. We also found that the acceleration data are the most important features. It implies the effectiveness of using acceleration sensors to predict student effort.

A range of research procedures have been executed to overcome malware attacks. This research used a malware behavior observe approach on device calls on mobile devices operating gadget kernel. An application used to be mounted on mobile gadget to gather facts and processed them to get dataset. This research used data mining classification approach method and validates it using ten fold cross validation. MiMaLo is a method to normalize a dataset the usage of the min-max aggregate and logarithm function. The application of the MiMaLo method aims to increase the accuracy value. Derived from the experiments, the classifiers overall performance level used to be extensively increasing. The application of the MiMaLo method using the neural network algorithm produces an accuracy of 93.54% with AUC of 0.982.

This bibliometric study aims at exploring the publications on embodied cognition in China based on the China Net Knowledge Index (CNKI) database between 2005 and 2021. “Embodied cognition” were keywords used for searching relevant publications in CNKI, November 6th, 2021. There are 1107 articles collected excluding English literature, conference papers, and dissertations. The free software BICOMB 2.0 is applied for data analysis. Results indicated that the number of articles is on the rise yearly since 2005. Most of the articles are seen in the core journals. The leading authors are Hao-sheng Ye, Wei Chen, and Xun-dong Zheng. The 211 level universities in China published more articles than other institutions. There are 5 major clusters representing hotspot issues: embodied cognition in linguistics, the pedagogical application of embodied cognition, cognitive psychology and the study of the embodied mind, the design of teaching environment with embodied cognition, and psychology and cognitive science. The research of embodied cognition in China is still in theoretical discussion, lacking empirical research. Thus, the interdisciplinary applications of embodied cognition in education and the theory of emotional personalization are potential issues in future research. The significance and value of this study tempts to summarize the hotspots and development trends in the field of embodied cognition in China on the basis of literature visualization with the help of scientific knowledge mapping technology, in order to provide some reference for researcher.

Coding for pupils has become a new trend in information communication technology (ICT) education as it is a gateway to the new digital era for future generations where computers are one of the backbones of modern society. In this respect, the present study aimed at investigating the usefulness and impact of teaching coding through “Scratch” (i.e., a coding software for pupils) on Moroccan pupils, measuring their capacity to learn coding and finally exploring Moroccan teachers’ perceptions about it. Therefore, a pre-test post-test experimental course study took place targeting 38 pupils of the 6th grade in a rural area school. The control group (19 participants) was not taught the basics of Scratch coding while the experimental group (19 participants) was taught through practical Scratch coding initiation lessons based on the theory-based model for computer programming teaching. Furthermore, a quantitative survey questionnaire was used to gather 5th and 6th grade teachers (202 participants) perceptions about Scratch. The Statistical Package for Social Sciences was used to analyze the data. The results of the quantitative questionnaire showed that Moroccan teachers endorse Scratch teaching for its potential benefits while the experimental study results proved that computer coding can be easily be integrated in Moroccan schools. The software is suitable for the students since they demonstrated significant interest in coding and have experienced positive impacts on various competencies.

By and large, software testing can be well thought-out as a adept technique of achieving improved software quality as well as reliability. On the other hand, the eminence of the test cases had significant effect on the fault enlightening competence of testing activity. Prioritization of Test case (PTC) remnants one challenging issue, as prioritizing test cases remains not up in the direction of abrasion by means of respect to Faults Detected Average Percentage (FDAP) and time execution results. The PTC is predominantly anticipated to scheme assortment of test cases in accomplishing timely optimization by means of preferred properties. Earlier readings have been presented for place in order the accessible test cases in upsurge speed the fault uncovering rate in testing. In this phase, this learning schemes a Modern modified Harris Hawks Optimization centered PTC (M2H2O-PTC) method for testing. The anticipated M2H2O-PTC method aims to exhaust the possibilities the FDAP and curtail the complete execution time. Besides, the M2H2O algorithm is considered for boosting the examination and taking advantage abilities of the conservative H2O algorithm. For validating the enhanced efficiency of the M2H2O-PTC method, an extensive variety of simulations occur on contradictory standard programs and the outcomes are inspected underneath numerous characteristics. The investigational results emphasized enhanced proficiency of the M2H2O-PTC method in excess of the modern methodologies in standings of dissimilar measures.