Ali Erkan

Data structure visualization with latex and prefuse

We report two ways with which data structures as well as their algorithmic operations can be visualized. The first method uses LaTeX to automatically generate diagrammatic presentation material from extended versions of the Java implementations of well-known ADTs. The second method uses the Prefuse API to explore objects created in running Java programs.

Sustainability themed problem solving in data structures and algorithms

During the past two years, we have been creating curricular material centered around complex problems rooted in sustainability. Since multi-disciplinary learning is one of our primary goals, these projects are most meaningful when they connect students from different disciplines working toward a common understanding. However, strong disciplinary components present in their solutions also allow us to frame these projects from strictly disciplinary perspectives. In this paper, we show how they can be used for increased engagement in the context of data structures and algorithms. We review two new ones to explore (i) the structural characteristics of the western part of the U.S. power-grid, and (ii) the effects of over-harvesting on fish stocks.

Use of satellite imagery in multidisciplinary projects

The most important problems of our century require collaborative work. Therefore, as educators, we must be producing individuals who understand how to communicate and work with professionals from other fields. In this paper, we outline our ongoing efforts in addressing this need, without compromising discipline specific qualities or goals. Specifically, we present a number of programming projects that fulfill curricular requirements as well as making students aware of the Science Technology Engineering and Math (STEM) context of their work.

Exposure to research through replication of research: a case in complex networks

This paper is primarily about introducing students to research. Specifically, we present a method where students get to redo the simulations behind a few of the most cited research papers in complex networks. We also outline the design of a course that provides the context for this experimentation.

Algorithms + Organization = Systems

Even though a computer science or computing-oriented de- gree is unavoidably broken into semesters and courses, we always hope that our students form a holistic picture of the discipline by the time they graduate. Yet we do not have too many opportunities to make this point in a convincing manner. This paper reports our e?orts to point out the connections between a seemingly (in the eyes of students) disconnected subset of courses in our degree requirements. In particular, we report on how we have used research papers as the glue between topics covered in our algorithms and sys- tems oriented courses (such as Organization and Computer Networks). Our assessment of the course has shown that students have not only made gains in their understanding and appreciation of meaningful intra-disciplinary connec- tions, but have also advanced in designing empirical experi- ments (mimicking the methodologies observed in the chosen papers) and reading/writing technical papers.

Using sustainability themes and multidisciplinary approaches to enhance STEM education

Purpose – The purpose of this paper is to report on the Multidisciplinary Sustainability Education Project (MSEP) as a framework using sustainability-themed education modules to introduce students to the need for multidisciplinary approaches to solving twenty-first-century problems while retaining traditional course strengths and content. Design/methodology/approach – The MSEP uses sustainability-themed education models and a multidisciplinary approach to link courses across disciplines. Modules are identified by an overarching question with activities designed to address the overarching question from course-specific perspectives, resulting in students writing short technical reports summarizing their results. Students then read and evaluate technical reports from other classes, and complete a summary activity designed to connect perspectives from different disciplines. Findings – The multi-method assessment identified no loss or gain in discipline-specific learning; increased understanding about the char...

Go Figure: Calculus Students' Use of Figures and Graphs in Technical Report Writing

Understanding how to read and use graphs to communicate scientific and mathematical in-formation is critical for STEM majors, as well as an important part of quantitative literacy. Ourstudy suggests that first-semester calculus students do not know how to use graphs in a technicalreport without explicit instruction. Although not a surprising result, it leaves us wondering aboutwhen such skills are developed, and if calculus I is a place to start. Our work is now exploringthe potential benefit on students’ use of graphs by having them formally evaluate other students’reports.KEYWORDS: Calculus, Technical Writing, Quantitiative Literacy

Educating the educator through computation: what GIS can do for computer science

We designed a system where non-computational faculty members (along with undergraduates) enroll in an introductory, multidisciplinary, open source Geographic Information System (GIS) course to experience integrative learning as students. The faculty participants are subsequently required to integrate their newly acquired expertise with their own disciplinary teaching and research; the necessary time commitment is compensated by a three-credit teaching load reallocation. Our hypothesis is that increasing the general facultys appreciation of computation (in the context of integrative learning) is an indirect yet effective and scalable way to reach a wider group of students to convey our fundamental disciplinary message: computing is more than programming and computing empowers people.

An image background detection project for a visual exploration of DFS and BFS

We outline a Data Structures project that visualizes the operation of depth first search (DFS) and breadth first search (BFS). We use color to illustrate how these two techniques differ as they traverse a search space. We present additional exercises that outline how students can further explore the underlying data structures, algorithmic concepts, and efficiency issues. We also provide a limited amount of student assessment to gauge the effectiveness of our approach.

Developing a Holistic Understanding of Systems and Algorithms through Research Papers

Even though a computer science or computing-oriented degree is unavoidably broken into semesters and courses, we always hope that our students form a holistic picture of the discipline by the time they graduate. Yet we do not have too many opportunities to make this point in a convincing manner. The goal of this working group will be to address a well-defined portion of this problem: revealing the significant connections between algorithmic courses (such as Discrete Math, Data Structures, Algorithms) and systems oriented courses (such as Organization, Computer Networks, Operating Systems, and Hardware) that may be missed by students. In particular, we will explore how research papers can be used as the glue for this purpose. The objectives of this working group are to identify crucial systems topics, locate papers of the appropriate nature, and categorize algorithmic concepts necessary to master the papers. Most importantly, we will create a framework to design combined systems/algorithm courses that hinge on the selected papers. Consequently, instead of using papers in the conventional manner to expose students to research, we will focus on how papers can be used to express the holistic structure of a conventional computer science or computing-oriented degree.