skip to main content

Title: MRS: Automated Assessment of Interactive Classroom Exercises
Classroom formative assessment augmented with timely and frequent feedback has become one of the most prominent teaching practices in education research. On the context of Computer Science (CS) courses that expose students to the functionality and dynamic aspects of various algorithms, traditionally, students are evaluated by exploring in-class paper-based exercises. In these exercises, they simulate the steps of an algorithm by drawing several instances of a diagram. This traditional approach is time consuming, is inherently difficult for students to express the dynamics of an algorithm, does not allow timely feedback, and restricts the number of exercises that students can practice and receive feedback on. Mobile Response System (MRS) is a software environment that facilitates in-class exercises and their real-time assessment using mobile devices and therefore focuses on addressing many of the above-mentioned problems. In this paper, we present results of eight semester-long studies using MRS in two of the required CS courses at Winston-Salem State University (WSSU). Our experimental evaluation shows the educational benefits of the proposed approach in terms of enhanced student retention of covered concepts, reduced failing rate, and increased student engagement and satisfaction.
; ; ;
Award ID(s):
Publication Date:
Journal Name:
49th ACM Technical Symposium on Computer Science Education
Page Range or eLocation-ID:
290 to 295
Sponsoring Org:
National Science Foundation
More Like this
  1. To improve student's class experience, the use of mobile devices has been steadily increasing. However, such use of mobile learning environments in the class is mostly static in nature through content delivery or multiple choice and true/false quiz taking. In CS courses, we need learning environments where students can interact with the problem in a hands-on-approach and instructor can assess their learning skills in real-time with problems having different degree of difficulty. To facilitate such interactive problem solving and real-time assessment using mobile devices, a comprehensive backend system is necessary. This paper presents one such system, named Mobile Response System (MRS) software, associated interactive problem-solving activities, and lessons learned by using it in the CS classrooms. MRS provides instructor with the opportunity of evidence-based teaching by allowing students to perform interactive exercises in their mobile devices with different learning outcomes and by getting an instant feedback on their performance and mental models. MRS is easy-to-use, extensible and can render interactive exercises developed by third-party developers. The student performance data shows its effectiveness in increasing student understanding of difficult concepts and the overall perception of using the software was very positive.
  2. In recent years, interactive textbooks have gained prominence in an effort to overcome student reluctance to routinely read textbooks, complete assigned homeworks, and to better engage students to keep up with lecture content. Interactive textbooks are more structured, contain smaller amounts of textual material, and integrate media and assessment content. While these are an arguable improvement over traditional methods of teaching, issues of academic integrity and engagement remain. In this work we demonstrate preliminary work on building interactive teaching modules for data structures and algorithms courses with the following characteristics, (1) the modules are highly visual and interactive, (2) training and assessment are tightly integrated within the same module, with sufficient variability in the exercises to make it next to impossible to violate academic integrity, (3) a data logging and analytic system that provides instantaneous student feedback and assessment, and (4) an interactive visual analytic system for the instructor to see students’ performance at the individual, sub-group or class level, allowing timely intervention and support for selected students. Our modules are designed to work within the infrastructure of the OpenDSA system, which will promote rapid dissemination to an existing user base of CS educators. We demonstrate a prototype system usingmore »an example dataset.« less
  3. Mobile devices are being used profusely in the classrooms to improve passive learning environments and to enhance student comprehension. However, with respect to students’ active involvement in problem solving activities, the typical usage of the mobile devices in answering multiple choice and true/false questions is not adequate and the use of mobile devices need to be expanded to include dynamic and interactive problem-solving activities to better satisfy students’ learning needs. To facilitate such interactive problem solving using mobile devices, a comprehensive software environment is necessary. This paper details the design, deployment and evaluation of Mobile Response System (MRS) software that facilitates execution and assessment of multi-step in-class interactive problem-solving activities using mobile devices. MRS is an active learning tool, which engages students with the visual representation of a problem that spans on multiple screens, allows them to interact with that, and makes them realize the consequences of their actions instantly and visually. The immediate and automated grading feature of MRS enables a feedback-driven and evidence-based teaching methodology, which is important to improve the quality of classroom learning. MRS is designed to be independent of any interactive problem or its domain. Therefore, it allows easier integration of interactive activity Apps developedmore »by others and can be used in any discipline. The results obtained from software metrics and runtime performance data verified the quality of the software. Additionally, the in-class assessment data verified that the MRS software is a helpful intervention for improving student comprehension and satisfaction.« less
  4. This poster addresses a significant learning barrier experienced at many CS departments, specially at predominantly minority institutions, which is the problem of students? inability to keep engaged and interested in classroom. In this research, we investigate the applicability of using mobile devices in the classroom and incorporation of interactive problem solving using those devices to increase class engagement and active learning for students. By allowing the students to solve problems in their preferred devices, the research expects to create a friendly learning environment where the students want to retain, be active and skillful. The poster will present the design aspects of Mobile Response System (MRS) software that will be utilized to communicate, collaborate and evaluate interactive problems using mobile devices. The poster will also showcase several interactive problem-solving activities utilizing mobile devices and MRS software, which have been developed and are being adopted in CS and IT courses at Winston-Salem State University (WSSU). It is expected that this research will invigorate interest in Computer Science among minority and underrepresented students through exposure to the technology-rich learning environment. By enhancing student learning and problem solving abilities, it is also expected that this research work will improve the quality and quantity ofmore »underrepresented minority students in STEM workforce or graduate study. The successful execution of this project will advance research and the knowledge of mobile device usage in CS classrooms and more importantly the way it impact teaching strategy and student learning at WSSU and other institutions.« less
  5. Peer assessment, as a form of collaborative learning, can engage students in active learning and improve their learning gains. However, current teaching platforms and programming environments provide little support to integrate peer assessment for in-class programming exercises. We identified challenges in conducting such exercises and adopting peer assessment through formative interviews with instructors of introductory programming courses. To address these challenges, we introduce PuzzleMe, a tool to help Computer Science instructors to conduct engaging in-class programming exercises. PuzzleMe leverages peer assessment to support a collaboration model where students provide timely feedback on their peers' work. We propose two assessment techniques tailored to in-class programming exercises: live peer testing and live peer code review. Live peer testing can improve students' code robustness by allowing them to create and share lightweight tests with peers. Live peer code review can improve code understanding by intelligently grouping students to maximize meaningful code reviews. A two-week deployment study revealed that PuzzleMe encourages students to write useful test cases, identify code problems, correct misunderstandings, and learn a diverse set of problem-solving approaches from peers.