Basic programming is a fundamental subject that contains basic materials of programming algorithms as well as the design and developing programs using programming languages. Based on observations in Vocational High Sc...
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ISBN:
(纸本)9781450366397
Basic programming is a fundamental subject that contains basic materials of programming algorithms as well as the design and developing programs using programming languages. Based on observations in Vocational High School at Indonesia, discovered some problems in the learning process of basic programming subject. Students are too focus with syntax errors, operating procedures and instructions of the programming language rather than understanding and practicing the related algorithms. Furthermore, learning resources used in the class are text modules which are not interactive and don't visualize abstract concept of programming language which could help students to understand the subject better. This research aims to design and improve Visual Programming Environment as Learning Support System on basic programming subjects. With this, students could put more focus in practicing design algorithms. It would be easy to sharpen their knowledge and understanding about basic programming without having to suffer from problems mentioned before.
This paper presents the evolution experienced by GreedEx, an interactive application to learn greedy algorithms. It shows the four different versions currently available. A first original version for computers, two ve...
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This paper presents the evolution experienced by GreedEx, an interactive application to learn greedy algorithms. It shows the four different versions currently available. A first original version for computers, two versions for iPad, and another version for smartphones. Besides, it describes the evaluation performed for each version, which has served so as to justify such evolution.
The theoretical background to automata and formal languages represents a complex learning area for students. Computer tools for interacting with the algorithm and interfaces to visualize its different steps can assist...
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The theoretical background to automata and formal languages represents a complex learning area for students. Computer tools for interacting with the algorithm and interfaces to visualize its different steps can assist the learning process and make it more attractive. In this paper, we present a web application for learning some of the most common algorithms in an appealing way. They are specifically linked to the recognition of regular languages that are, taught in classes on both automata theory and compiler design. Although several simulators are available to students, they usually only serve to validate grammars, automata, and languages, rather than helping students to learn the internal processes that an algorithm can perform. The resource presented here can execute and display each algorithm process, step by step, providing explanations on each step that assist student comprehension. Additionally, as a web-based resource, it can be used on any device with no need for specific software installation.
Understanding the behaviour of algorithms is a key element of computer science. However, this learning objective is not always easy to achieve, as the behaviour of some algorithms is complicated or not readily observa...
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ISBN:
(纸本)9781538633717
Understanding the behaviour of algorithms is a key element of computer science. However, this learning objective is not always easy to achieve, as the behaviour of some algorithms is complicated or not readily observable, or affected by the values of their input parameters. To assist students in learning the multilevel feedback queue scheduling algorithm (MLFQ), we designed and developed an interactive visualization tool, Marble MLFQ, that illustrates how the algorithm works under various conditions. The tool is intended to supplement course material and instructions in an undergraduate operating systems course. The main features of Marble MLFQ are threefold: (1) It animates the steps of the scheduling algorithm graphically to allow users to observe its behaviour;(2) It provides a series of lessons to help users understand various aspects of the algorithm;and (3) It enables users to customize input values to the algorithm to support exploratory learning.
In my research, I will explore the potential of adapting the literature on algorithm visualization and visual analogy to the teaching of concepts and computations in introductory data science. Using computerized tutor...
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ISBN:
(纸本)9781450356282
In my research, I will explore the potential of adapting the literature on algorithm visualization and visual analogy to the teaching of concepts and computations in introductory data science. Using computerized tutorials informed by the extensive literature on multimedia principles already available, I will explore if a visual pseudo-code facilitates simulation and application of data algorithms, beyond the facilitation afforded by mathematical notation. The research will combine between-subject classroom interventions with distance learning and within-subject laboratory studies. The dissertation will give fine-grained evidence on which types are more effective and how it could be implemented in the community at large. I am primarily interested in discussing methodological issues relating to how to make comparisons in such a multi-dimensional design space.
A parsing algorithm visualizer is a tool that visualizes the construction of a parser for a given context-free grammar and then illustrates the use of that parser to parse a given string. Parsing algorithm visualizers...
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A parsing algorithm visualizer is a tool that visualizes the construction of a parser for a given context-free grammar and then illustrates the use of that parser to parse a given string. Parsing algorithm visualizers are used to teach the course on compiler construction which in invariably included in all undergraduate computer science curricula. This paper presents a new parsing algorithm visualizer that can visualize six parsing algorithms, viz. predictive parsing, simple LR parsing, canonical LR parsing, look-ahead LR parsing, Earley parsing and CYK parsing. The tool logically explains the process of parsing showing the calculations involved in each step. The output of the tool has been structured to maximize the learning outcomes and contains important constructs like FIRST and FOLLOW sets, item sets, parsing table, parse tree and leftmost or rightmost derivation depending on the algorithm being visualized. The tool has been used to teach the course on compiler construction at both undergraduate and graduate levels. An overall positive feedback was received from the students with 89% of them saying that the tool helped them in understanding the parsing algorithms. The tool is capable of visualizing multiple parsing algorithms and 88% students used it to compare the algorithms.
In this paper, first we present an educational system that assists students in learning and tutors in teaching search algorithms, an artificial intelligence topic. Learning is achieved through a wide range of learning...
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In this paper, first we present an educational system that assists students in learning and tutors in teaching search algorithms, an artificial intelligence topic. Learning is achieved through a wide range of learning activities. algorithm visualizations demonstrate the operational functionality of algorithms according to the principles of active learning. So, a visualization process can stop and request from a student to specify the next step or explain the way that a decision was made by the algorithm. Similarly, interactive exercises assist students in learning to apply algorithms in a step-by-step interactive way. Students can apply an algorithm to an example case, specifying the algorithm's steps interactively, with the system's guidance and help, when necessary. Next, we present assessment approaches integrated in the system that aim to assist tutors in assessing the performance of students, reduce their marking task workload and provide immediate and meaningful feedback to students. Automatic assessment is achieved in four stages, which constitute a general assessment framework. First, the system calculates the similarity between the student's and the correct answer using the edit distance metric. In the next stage, it identifies the type of the answer, based on an introduced answer categorization scheme related to completeness and accuracy of an answer, taking into account student carelessness too. Afterwards, the types of errors are identified, based on an introduced error categorization scheme. Finally, answer is automatically marked via an automated marker, based on its type, the edit distance and the type of errors made. To assess the learning effectiveness of the system an extended evaluation study was conducted in real class conditions. The experiment showed very encouraging results. Furthermore, to evaluate the performance of the assessment system, we compared the assessment mechanism against expert (human) tutors. A total of 400 students' answers wer
Computer Science instructors have been exploiting learning technology such as algorithm visualization (AV) for last few years to explain hard-to-understand algorithms to the learners through simulations and animations...
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ISBN:
(纸本)9781450346986
Computer Science instructors have been exploiting learning technology such as algorithm visualization (AV) for last few years to explain hard-to-understand algorithms to the learners through simulations and animations. In this work, we explore an active and highly engaging approach, namely, the construction of visualizations of the algorithms under study. Our approach is further augmented with automated assessment of students' inclass construction activities, which they execute as apps in their mobile devices. In this paper, we utilize case study, a step-by-step visualization of a construction exercise app, to explain how technology is leveraged to provide a richer way for learners to interact with a problem, and how instructor can acquire real-time evidence of learners' comprehension of covered lecture material. Our experimental evaluation shows the educational benefits of the proposed approach in terms of enhanced student learning, reduced drop-out rate and increased student satisfaction.
When compared to earlier programming and data structure experiences that our students might have, the perspective changes on computers and programming when introducing theoretical computer science into the picture. Un...
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When compared to earlier programming and data structure experiences that our students might have, the perspective changes on computers and programming when introducing theoretical computer science into the picture. Underlying computational models need to be addressed, and mathematical tools employed, to understand the quality criteria of theoretical computer science. Focus shifts from doing to proving. Over several years, we have tried to make this perspective transition smoother for the students of a third-year mandatory algorithms, data structures, and computational complexity course. The concepts receiving extra attention in this work are NP-completeness, one of the most central concepts in computer science, and dynamic programming, an algorithm construction method that is powerful but somewhat unintuitive for some students. The major difficulties that we attribute to NP-completeness are that the tasks look similar but have a different purpose than in algorithm construction exercises. Students do not immediately see the usefulness of the concept, and hence motivation could be one issue. One line of attacking NP-completeness has been to emphasize its algorithmic aspects using typical tools for teaching algorithms. Some potential difficulties associated with dynamic programming are that the method is based on a known difficult concept-recursion-and that there are many ingredients in a dynamic programming solution to a problem. For both dynamic programming and NP-completeness, we have invented several new activities and structured the teaching differently, forcing students to think and adopt a standpoint, and practice the concepts in programming assignments. Student surveys show that these activities are appreciated by the students, and our evaluations indicate that they have positive effects on learning. We believe that these activities could be useful in any similar course. The approach to improving the course is action research, and the evaluation has been done u
Search algorithms constitute an important topic in the Artificial Intelligence curriculum and are acknowledged by most tutors to be a hard and complex domain for teachers to teach and students to deeply understand. In...
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ISBN:
(纸本)9789897581793
Search algorithms constitute an important topic in the Artificial Intelligence curriculum and are acknowledged by most tutors to be a hard and complex domain for teachers to teach and students to deeply understand. In this paper, we present an educational computer game, designed to teach search algorithms, based on the popular Pacman game. The purpose of the educational Pacman game is to assist students to understand the artificial intelligence topic of search algorithms in an entertaining, interactive and motivating way. During their experience with the game, students can examine the behaviour of various search algorithms and a graphical annotated depiction of them through suitable visualizations. visualizations can demonstrate the operational functionality of algorithms and are designed in line with the principles of student's active learning. Various learning activities were designed and request students to apply specific search algorithms in various example cases with or without the assistance and feedback of the game. An evaluation study was conducted in real classroom conditions and revealed quite satisfactory results. The results indicate that the educational Pacman game is an effective way to enhance students' engagement and help them to deeper understand the AI search algorithms.
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