Interaction and Feedback in Automatically Assessed Algorithm Simulation Exercises

Abstract

Executive SummaryFeedback is an essential element of learning. Students need feedback on their work and their solutions to assignments both when they work manually and while they use a computer. A number of tools have been implemented to automatically assess and give feedback, for example, on programming exercises and algorithmic exercises. However, one problem of the provided feedback is that in most cases its scope is too narrow to support the needs of different types of learners. For example, many systems provide purely verbal feedback.In this paper we consider how exercises with automa tic feedback should be designed to support a broader scope of learners. We discuss the Felder-Silverman learning model, which we use as the framework for our discussion. The model categorizes learners with four different axes: sensing vs. intuitive learners, visual vs. verbal learners, active vs. reflective learners, and sequential vs. global learners. We discuss how all dimensions of the model can be taken into account when designing assignments and automatic feedback. Moreover, we use two modern automatic assessment systems, PILOT and TRAKLA2, as example systems to demonstrate our ideas.We strongly believe that incorporating analysis of learners' preferences into design of courses, automatic feedback systems, and learning environments leads to better learning. As teachers, we should better support the needs of our students, and also train their skills to process information in more versatile ways.Our discussion concentrates on algorithmic assignments. However, in the conclusion we briefly illuminate how similar approach could be used to design better assignments and feedback for programming exercises, as well.

Autoevaluación del aprendizaje en enfermería con ejercicios interactivos del programa Hot Potatoes

“…Es indudable que al profesor le supone un trabajo adicional a la hora de establecer ejercicios de este tipo, pero por regla general tienen una aceptación muy buena por parte del estudiante, que en ocasiones espera ver la creatividad del docente [1]. Las valoraciones elevadas de los alumnos respecto a si los ejercicios habían facilitado su aprendizaje, si el método les había servido para adquirir conocimientos y si constituía un método útil como técnica de estudio coinciden con las aportaciones de otros trabajos, que indican que el uso de pruebas de autoverifi cación, si están bien pensadas y diseñadas, pueden contribuir a orientar el proceso de aprendizaje de los alumnos y ayudarles a comprobar si lo que están aprendiendo responde efectivamente a lo que se espera de ellos [13][14][15][16].…”

Usability and Pedagogical Assessment of an Algorithm Learning Tool: A Case Study for an Introductory Programming Course for High School

“…The more popular ones are: (1) ANIMAL (A New Interactive Modeler for Animations in Lectures) (Rößling, Schüler, & Freisleben, 2000); (2) JAWAA (Java And Web-based Algorithm Animation) (Pierson & Rodger, 1998); (3) JHAV´E (Java-Hosted Algorithm Visualization Environment)-another Java-based system and runs on a client-server environment (Naps, Eagan, & Norton, 2000); and (4) TRAKLA2-a project of the Software Visualization Group at Helsinki University of Technology (Korhonen, Malmi, & Silvasti, 2003).…”

HOW DOES ALGORITHM VISUALIZATION AFFECT COLLABORATION? - Video Analysis of Engagement and Discussions

“…TRAKLA2 is a practicing environment for visual algorithm simulation exercises (Korhonen et al, 2003;Malmi et al, 2004) that are automatically assessed tracing exercises solved by a student in a web-based learning environment. The system distributes individually tailored exercises to students and provides instant feedback on students' solutions.…”