Online assignment submission delay as a behavioral indicator of procrastination.

Technology has made a significant impact on assessment, including its use to automate assignment submission. On-line assignment submission, marking, and return were introduced into a fourth-year engineering management unit for the first time, and a formal evaluation was undertaken to assess student perceptions of this new development. Nearly all respondents understood how to submit their assignments on-line. More than 80% of respondents understood how to retrieve their assignment marks on-line, but only just over half that proportion understood how to get their assignment comments/ feedback. More than 80% of respondents felt that their assignments were returned faster on-line. Respondents rated the ease of use of the on-line assignment submission system highly. Speed, timeliness, and convenience of operation were reported as positive aspects. The most commonly reported negative aspects related to an arbitrary assignment submission file size limitation that forced some students to reconsider their use of large graphic images.

Technology has made a significant impact on assessment, including its use to automate assignment submission. All processes in the workflow - submission of assignments, assessment, and feedback given are performed using electronic files. Online assignment submission was introduced at the College of Health Sciences (CHS), University of Bahrain (UoB) in 2008 through the Learning Management System. This research attempts to answer two questions: Firstly, what are the perceptions of the CHS instructors and students about the use of online assignment submission? Secondly, what challenges do instructors and students encounter in using online assignment submission at the CHS? One hundred and forty (140) students from different programs at the College have participated in this study. Ninety six (96%) of the CHS students had very good computer skills and e-learning experience and 63% of the students reported familiarity with online assignments during their study period at the CHS. Eighty percent (80%) of students prefer to submit and to get their assignments grades online. Also, eighty three percent (83%) think that online assignment submission is quicker than the hard copy submission. Eight (8) teaching faculty from the Integrated Sciences Department participated in the interviews. The interview results revealed that although most teaching faculty have good skills in using computers and its applications, they prefer to use traditional teaching methods with increased dependence on computer applications. They also believe that the Web based programs with supporting materials such as online assignments, animations, and videos support the teaching process and make learning more enjoyable.

This paper presents the results of a study evaluating student perceptions of online assignment submission. 47 students submitted assignments and received feedback via features within the Virtual Learning Environment Blackboard™. The students then completed questionnaires comparing their experience of online submission and feedback with traditional methods.Results indicated that 88% of students reported a time saving and many reported financial benefits using online submission. 93% of students preferred having their feedback available online rather than printed and handed to them. Overall, students preferred online assignment management to postal or physical hand‐in. The main disadvantage of electronic submission appeared to be student distrust of the receipt system.The use of online assignment submission and management is recommended for use in Higher Education establishments where students may be remote. It is most suitable for assignments that do not require inclusion of many images.

Online course management system (OCMS) mainly aids various events in online instructing, including testing, course discussion, assignment submission, and assignment grading. This paper is mainly designed basing on the study of completed OCMS of the past. Online assignment submission is prone to easy plagiarism, infecting the learning process of the students and interfering with their studies. In the past, using human power to inspect for plagiarism is very time-consuming. This research then is focused on allowing programming courses to employ procedures such as code standardization, textual analysis, structural analysis, and variable analysis, to evaluate and compare programming codes. We provide an intelligent agent as a daemon to analyze the program code for OCMS. Textually, we use document fingerprinting algorithm as a basis for text comparison; structurally, we utilize formal algebraic expression and dynamic control structure tree (DCS tree) to rebuild and evaluate the program structure; variable-wise, we not only record relevant information for each variable, but also analyze the programming structure where the variables are positioned. By applying a similarity measuring method, we output a similarity value for each program in the three aspects mentioned above. This research implements a convenient user interface that can be applied independently for assignment analyzation. Moreover, we have designed a set of application programming interface (API) that could be embedded into online course management systems.

The use of technology as a teaching tool at the university level is becoming increasingly popular. Graduate students aspiring to become educational leaders engage in weekly on-line discussions and assignment submissions through various platforms. These graduate students are also employed by school districts as classroom teachers. Over one semester, graduate students' electronic submissions of assignments in six courses were monitored to review the time of day during which students were submitting assignments. Results of the monitoring revealed that 51% of their assignments were submitted during the school day, thus creating an ethical dilemma for both the students and professors who are receiving the assignments. Who's managing their classrooms while teachers are submitting assignments on-line for their graduate courses?

Objective: To implement online assignment submission with instant feedback in a biopharmaceutics course taught to professional pharmacy students, and to evaluate students’ reception of the activity. Method: Online assignments equipped for immediate grading and feedback were administered on Blackboard to second year pharmacy students. A survey assessing students’ reception of the effectiveness of this method was administered at the end of the semester. Results: Almost all the students (99.1%) agreed or strongly agreed that the online assignments and feedback improved their understanding of the basic concepts in the course. Students (98.8%) also felt that the use of computers in the course was worthwhile, and recommended their continued use. Conclusion: Online assignments with instant feedback offers a readily workable technique that students and this author perceive to have great value for enhancing student understanding in biopharmaceutics and related pharmacy courses.

My journey in technology enhanced education within engineering to achieve sustainability amidst disruptions

An international association advancing the multidisciplinary study of informing systems. Founded in 1998, the Informing Science Institute (ISI) is a global community of academics shaping the future of informing science.

Understanding the factors that affect continued use or discontinuance of an information system beyond initial adoption is one of the most challenging issues in information systems research. This paper combines information economics, the technology acceptance model (TAM), and diffusion of innovation theory, and analyzes barriers with respect to the continued use of information systems. The suggested model examines data collected from 284 former users enrolled in a blended distance learning university, who apparently abandoned an online assignment submission system. The findings indicate that behavioral intention to use the system was mainly influenced by its perceived ease of use, perceived usefulness, its real value, and general attitude towards new technologies. Social and institutional influence was quite low, but the major barrier to continuance was incompatibility with the assignment preparation process performed by the students, as well as the assignment checking process performed by the tutors, which discouraged continued use.

Relations between faculty use of online academic resources and student class attendance

The web-based learning platform provides quality education nowadays, but assignment submission is a critical issue in the e-learning system. Therefore, to investigate assignment submission of the student in advance before the end of course is an important problem. The assignment submission prediction is the advantage of the e-learning system because it allows the instructor to find students’ problems on time. Additionally, online learning mostly depends on demographic characteristics such as region, age, and education level. This study uses machine learning (ML) methods to detect students who do not submit assignments on time and then also find which demographic factors affects online assignment submission. The data is publicly available and was collected from an open university of U.K. The result shows that Random Forest is an optimal option for predicting students who do not submit an assignment on time. We have also found that Gender, Student Credit, Final result, Total clicks, Score are strong predictors for student assignment.KeywordsMachine learningE-learningStudent assignmentFeature extractionClassification

The Open Assignment Submission (OAS) is an innovative regime whereby students submit homework assignments of an appropriate nature into a designated open forum provided by the Learning Management System (LMS). Our previous research, carried out with a cohort of Education graduates, indicated possible benefits and challenges of OAS as a means of supporting assignment submission through learning from peer examples. The current paper presents a recent explorative case study into the behaviour patterns and views of 55 first year students regarding OAS, during the very early stages of the Academic Literacy course. Drawing on two main data sources (a self-report questionnaire and data of student access and submission retrieved from the course LMS records) we have found characteristic patterns of peer-example viewing, assignment submission schedules and related grades. The OAS regime appears to provide an appreciated learning support and has a potential to promote intentional learning.

This study aims to evaluate the implementation of Google Classroom in learning at SD Mathlaul Anwar and its impact on student engagement, ease of managing learning, and student learning outcomes. Google Classroom, as an online learning management platform, enables more effective interaction between teachers and students, as well as facilitates the management of materials and assignments. This research uses a descriptive qualitative approach, with data collection through literature review, interviews with fifth-grade teachers, and observations of the platform's implementation in learning. The results show that Google Classroom provides significant benefits, such as easy access to learning materials, increased student participation, and efficient class management. Features such as online assignment submission, automatic reminders, and discussion rooms enable a more structured and collaborative learning process. However, the main challenges faced are the dependence on stable internet access and adequate devices. Nevertheless, these challenges can be overcome with training sessions for students and parents. This study concludes that Google Classroom can improve student learning outcomes, provide space for independent learning, and contribute to the creation of a more interactive and collaborative learning environment. The future use of Google Classroom is expected to be further optimized to support both face-to-face and remote learning with the development of new features that support project-based and interactive video learning.

: In this cyber-driven world, assignments are submitted by higher education students by using pen, paper and pencil. With the outbreak COVID-19, the smart phones, tablets and computers/laptops play a vital role in educating the school students as well as higher education students. Despite the fact that the current generation students' skill development is through additional education modes like assignments, formative assessment, and model-based assignments and so on, the teaching and learning process remains old. Very few educators are using smart education tools to collect feedbacks, to assess student's knowledge using open CV's like Padlet, Plickers, Moodle and Google classroom. The introduction of online assignment submission enriches the student's skills, knowledge and content development skills. In this paper, the student's activities for submission of assignment and subject content clarification are performed using Google classroom as an interactive tool. The introduction of online assignment submission creates measurable difference in student's performance over traditional assignment submission.Although the student's performance, student characteristics and study behavior are explained using case study on Mechatronics system Design course and its impact on the students for further improvement in education system. Keywords: Peer teaching, online assignment, Google classroom, Mechatronics system design

The rapid advancement of technology has created new opportunities to enhance education, with machine learning (ML) emerging as a transformative tool. This study presents the development and evaluation of a comprehensive academic tracking system designed to monitor and categorize students based on performance metrics, while also providing functionality beyond simple grade reporting. Unlike traditional systems that serve primarily as repositories for academic scores, the proposed system offers integrated tools for tracking attendance, monitoring academic progress, managing assignments, and generating early alerts for at-risk students. Developed using Python for backend logic, React for frontend implementation, and MySQL for secure data management, the web-based platform was designed to improve real-time access and usability for both students and educators. The system incorporates a multifaceted methodology to analyze a wide range of student-related factors, including demographic data (e.g., age, gender, socioeconomic background), academic performance (e.g., grades, attendance), and behavioral indicators (e.g., participation and assignment submissions). The model classifies students into low, average, and high-performing groups using machine learning techniques, enabling more targeted interventions. When tested with real academic data from tertiary institutions in Nigeria, the proposed system demonstrated superior accuracy and efficiency in tracking and predicting student performance compared to existing solutions. These findings underscore the system’s potential to support data-driven decision-making in educational environments and to enhance learning outcomes through early identification and personalized support strategies.