Muhammed Miah, Southern University at New Orleans
Ordered by presentation time
The Role of Teaching-Learning Style Fit and Content Complexity in Information Systems Courses
North Carolina A&T State University
Monday - 11/2/2015 in Bellamy at 9:50 am
It is common knowledge that engineering, computer science, and information systems course content have been often described as difficult to learn by most students. Content complexity associated with information is a function of the number of causal links in a chain of actions, physical states, or mental states. Causal links between units of information are typically defined through the use of temporal (e.g., before, and then, after), causal (e.g., which caused, which enabled, because, if-then), or intentional (e.g., in order that, so that, to allow) connectives. As the number of causal links needed to convey an idea or concept increases (i.e., causal chain length), working memory becomes overloaded because it is limited in the number of related ideas that can be simultaneously stored and processed. According to cognitive load theory, all cognitive processing and learning occurs through a very limited working memory and an unlimited long-term memory to structure a set of hierarchically ordered schemas. Cognitive load theory suggests that “how” information is presented (i.e. teaching style) to students will impact working-memory load and thus be a critical factor in determining learning success. If the cognitive load exceeds the limits of working memory, then learning will be hindered.
Learning styles theories define learning as a cognitive process that entails the use of encoding, processing, and synthesis of information during a learning or problem solving task. The varied current learning style theories/models view the learning process and outcomes to be based on 1) learner motivations, 2) perception and processing of information, 3) sensory preferences, and 4) active demonstration with experiential immersion. [Read More]
A Comparison Study in Open Source Learning Management Software
Sam Houston State University
Sam Houston State University
Monday - 11/2/2015 in Dudley at 3:05 pm
Based on the demands of online teaching and learning programs from various levels of educational systems and enterprises in the past decade, there are many open source learning management systems from which to choose. In order to select the most feasible and appropriate learning management software, it requires the administrators to analyze and assess the needs from their own institutions and follow up with the comparison of available software. This study investigated three top leading learning management software including Moodle, Olat, and Sakai. These selected software offer easy access to demonstration and details of functionality.
The comparison for this research included the three categories of Course Building Functions, Server Functions, and Training and Service. For the Course Building Functions category, there were eight items compared for details of course quality control, interactive tools, template courses, gradebook interfaces, social network subscription, calendar builder, course assessment, and resources sharing. The available functions of monitoring criteria, interacting interfaces, and assessing tools were carefully scrutinized in this category. [Read More]
Teaching Business Analytics Using the caret Package in R
Bridgewater State University
Monday - 11/2/2015 in Skinner at 3:05 pm
R is a powerful, open source statistical programming environment that is becoming increasingly popular within the business community. The College of Business at Bridgewater State University recently piloted an “Introduction to Business Analytics using R” course which had only an introductory statistics course prerequisite. A major challenge of teaching such a course is covering R programming, new analytic techniques and the data analytics process. To meet this challenge, one approach is to focus on R programming by teaching students how to do tasks that they have already learned. This would include, for example, conducting t-tests and analyses of variance. A second approach is to focus on new analytical techniques and to minimize the burden of learning R by providing sample scripts that students can easily adapt for assignment completion. However, a drawback of the second approach which was used in the pilot course is that it is easy for students to become overly preoccupied with the details of particular implementations of particular techniques. [Read More]
Supply Chain Technology Evaluation: RFID vs. DataMatrix
Tuesday - 11/3/2015 in DeRosset at 9:45 am
This teaching case focuses on technology investment decision making for tracking and tracing of products in supply chains. Tracking involves recording how a product moves from supplier to the end customer (by capturing times, locations, ownership, temperature variations, etc.), while tracing involves retrieval of this data to support verification of product quality and provenance. Two major technologies for tracking and tracing in supply chains exist today: optical recognition of 2-D barcodes (with DataMatrix being one of the most widely known such codes), and radio-frequency identification, or RFID. At the back end, both technologies require a redesign of a company’s enterprise systems to capture, store and retrieve track and trace data, and analyze and transform it into actionable knowledge.
No unified global technology standard for tracking and tracing exists today. Country-level regulations for track and trace exist only in a handful of industries. For example, tracking and tracing is a regulatory mandate in the pharmaceutical industry in some parts of the world, but most countries, including the US, have not required the use of a specific technology in support of the regulations. [Read More]
How Do We Fit It All In?: Efficacy of Flipped Course Design in Lab-based, Introductory Information Systems Classes
University of North Carolina Wilmington
Tuesday - 11/3/2015 in Dudley at 9:45 am
Prior research has suggested that the flipped classroom approach might not be the best structure for an introductory course.  A specific challenge to flipping the classroom when teaching introductory topics is that the material that is taught might be heavily conceptual, making constructing active learning exercises difficult. When teaching introductory concepts and vocabulary in information systems, it can be challenging to incorporate cases and other active-learning activities. Students may not have enough knowledge of the subject to be able to engage in higher-order cognitive learning activities, such as application or analysis activities in Bloom’s taxonomy . Adding lab-based activities are a straightforward approach to provide active learning approaches to introductory material. Traditional hard sciences have handled this by effecting the four credit hour class, three hours conceptual and one hour lab-based.
Will Simulation Software Facilitate Case Analysis?
Tuesday - 11/3/2015 in McRae at 9:45 am
Abstract: Being able to choose and apply the appropriate decision analysis tools for business problem solving is a skill that will serve students well both in upper level courses and in their future careers. This requires analytical skills plus an understanding of the spreadsheet tools available and how they are applied. When teaching these skills, it is important to use a scenario representative of the business world. In an advanced undergraduate course in analytical computing using spreadsheets and databases, semi-structured and unstructured case studies are used for students to gain this experience. To address high course drop rates, and the perception that students did not understand the advanced skills they were expected to apply in the cases, Microsoft Office simulation software was added to the course. The intent was to give students more intense practice with new techniques before applying them to cases. Analysis of student performance and course retention rates appears to indicate that the simulation software has not been effective.
Description: Most students today are exposed to the basics of Microsoft Office at the secondary school level. In many colleges, they are also required to take an introductory course that covers the basic Microsoft Office components (Word, Excel, and PowerPoint).
National Cyber League Training and Collegiate Cyber Defense Competitions
University of North Carolina Wilmington
Tuesday - 11/3/2015 in Bellamy at 4:55 pm
Simulating the real world environment, Collegiate Cyber Defense Competitions (CCDCs) are designed to assess the knowledge and understanding of college students’ information assurance and computer security skills. During these competitions, student teams are given administrative and protective duties for an existing network. They need to manage their resources (hardware, people, time, skills, etc.) to maintain the availability of essential information technology (IT) services while they are simultaneously protecting their information assets against external threats. In order to be successful in CCDCs, students need to have proficiency in several areas including, but not limited to, network management, system administration, change management and incident response. Unfortunately, due to the lack of trained faculty and other additional resource constraints, nationally only a handful of schools are able to offer curriculums providing the skills necessary to compete in such an environment. The absence of an outlet prevents interested students, who could potentially be valuable future information security workforce members, have proper training and consequently participating in the educational experience the cyber defense competitions offer. This study aims to give an outline of how National Cyber League (NCL) could be utilized to prepare student teams to participate in collegiate cyber defense competitions.
Simulation in Business Education: A Literature Review
Tuesday - 11/3/2015 in DeRosset at 4:55 pm
The modern business world is increasingly complex, global, and dynamic. Preparing business students for success in this environment requires the use of teaching methods that build critical thinking skills in realistic situations. Simulation is one teaching tool that can be used to support this goal by mimicking the reality, through physical or computer-based models, in a controlled, complex, and collaborative setting. Apart from providing domain-specific knowledge, simulation can increase students’ interest and motivation, help them understand complex cause-effect relationships and develop leadership skills (Lainema & Lainema, 2007; Cronan & Douglas, 2011; Siewioreck, Saarinen, Lainema, & Lehtinen, 2012).
This study explores the use of simulation in business education, in general, and in the information systems (IS) discipline, in particular, through a literature review. We conducted a search of major bibliographical databases for articles containing “simulation,” “business” and “education” in the abstract, resulting in 122 relevant papers, published from 1995 to 2014. Three authors and a research assistant read and coded the articles (categories included year published, journal, business discipline, simulation type, simulation procedure and software (if any), pedagogical purpose, participants, etc.).
Student Perceptions of Introductory Database Concepts and Database Privacy Issues
North Carolina A&T State University
North Carolina A&T State University
Tuesday - 11/3/2015 in Dudley at 4:55 pm
Basic database concepts are a required component of the curriculum for information technology students. It is also often taught in introductory microcomputer applications classes that are taken by students from a variety of disciplines. Some faculty have questioned whether database concepts should be taught to non-technology majors. However, in the age of big data, teaching basic database concepts may be beneficial to all students so that they can better comprehend how big data can be accomplished and how it affects their personal lives, especially in terms of associated privacy issues. Little research has been conducted in how to teach introductory database concepts to students. Some research has applied cognitive load and transfer of learning theories to explore how students can learn database concepts in a sustainable and effective manner.
The purpose of this study is to further investigate cognitive load and transfer of learning theories and to: explore student perceptions about the importance of understanding databases in their professional lives, explore student perceptions about the importance of understanding databases in their private lives, and determine if, given different treatments, student perceptions of database concepts will different.
Specifically, in a group of students who were given a comprehensive project and who were privy to a discussion about database privacy issues, their self-perceptions about database concepts should be higher on the post survey than the group of students who only completed assignments from the book.
Maximizing Reverse Selection Queries
Southern University at New Orleans
Tuesday - 11/3/2015 in McRae at 4:55 pm
In recent years, research in query processing has changed a lot. It has moved from traditional query processing (e.g., Selection, Nearest Neighbor (NN), Top-k, Skyline), to reverse query processing (e.g., Reverse NN, Reverse Top-k, Reverse Skyline), to maximal reverse query processing (e.g., find spatial points that maximize the number of Reverse NNs), and so on. This study considers a novel problem in this research area: given a set of selection queries with conjunctive conditions, create a tuple that maximizes the number of queries that return this tuple in their answers; that means maximizing the query results for reverse selection queries Surprisingly, there is no prior work on this problem, even though it has several natural applications, such as selecting product features or choosing the topics of a blog. The NP-completeness of the problem will be proved. The study will develop efficient exact algorithms and theoretical approximation algorithm with provable error bounds as well as a scalable heuristic that works well in practice for larger datasets. The study will conduct extensive experiments on real and synthetic data to demonstrate the effectiveness of the proposed algorithms.