The issue of missing persons remains a significant concern in the United States, with thousands of cases reported annually. Addressing this challenge requires innovative methods to integrate and analyze disparate data sources to uncover patterns in disappearances. This research explores the potential of Ontology Engineering and Knowledge Graphs to provide a structured and interconnected perspective on missing person data. Ontologies enable the representation and linking of real-world entities within a unified framework, facilitating more meaningful data relationships.In this study, a knowledge graph is constructed to capture key details about missing persons, including the circumstances of their disappearance, personal characteristics, and last known locations. Additionally, a Large Language Model (LLM) is integrated to summarize query results, enhancing data interpretation. This knowledge graph serves as a foundation for advanced data analysis, enabling real-time insights, supporting proactive interventions, and aiding in case resolution.

Modern travel planning requires knowledge graphs (KGs) that semantically integrate heterogeneous datasets while prioritizing niche attractions and real-world constraints. This paper introduces a Travel Planning Knowledge Graph (KG-ITP) combining Geographic Names Information Systems (GNIS) natural features, Institute of Museum and Library Services (IMLS) cultural sites, Yelp dining taxonomies, and Valley Metro transit networks through schema alignment and OWL2 ontological modeling. The KG-ITP’s novel architecture establishes spatial-temporal dependencies between activities (e.g., museum hours), transit accessibility (e.g., light rail buffers), and user constraints (e.g., dietary needs) using a query language for processing geospatial data called GeoSPARQL, its proximity functions and Resource Description Framework (RDF).By resolving semantic conflicts between authoritative and crowd-sourced datasets, the knowledge graph improves coverage of underrepresented attractions often omitted by commercial platforms through semantic alignment and spatial reasoning. The prototype implementation of the travel planner system demonstrates efficient query processing of complex multi-criteria requests like identifying vegetarian-friendly restaurants within 500m of transit-accessible cultural sites. The modular design enables seamless integration of third-party datasets through shared vocabularies. This work contributes to tourism informatics by illustrating how ontology-driven knowledge graphs can enhance personalization accuracy compared to traditional keyword-based systems while maintaining W3C standards compliance for spatial-semantic reasoning.

This Innovative Practice Full Paper presents an analysis of autograder usage on software engineering design outcomes. Autograders have found increasing use in software engineering and computer science courses due to a variety of reasons. They are often introduced to support large class sizes, increase the reproducibility of grades, and provide formative feedback to students. Many of the classes that apply autograders are introductory in nature, such as CS1 and CS2 courses, or an introduction to algorithms course. These courses typically focus on assessing student programming ability on specific aspects of a programming language (e.g., Java inheritance) or algorithms (e.g., sorting, searching). One common drawback to automated assessment with programming is the need to impose additional structure on assignments. For example, students asked to implement a game might be given a detailed list of functions to implement, skipping analysis and design to determine what functions and algorithms are relevant. In this work, we discuss the experience of introducing an autograder into a second-year course that teaches software engineering topics such as personal software process, object-oriented design, and UML. Although we have the traditional motivations to use an autograder, it is challenging in a software engineering course since the additional structure required by an autograder is potentially detrimental to the engineering design outcomes. To address this, we developed an autograder in such a way as to minimize the design choices that it imposed on the students. The partial structure that is imposed together with the formative feedback produced by the autograder helps to scaffold student learning as they transition to more complex programs. The autograder was used during a spring 2023 offering of our software engineering course. We analyzed the data gathered in this course to evaluate the course change by asking: how does introducing an autograder impact course design outcomes? And, how does introducing an autograder impact personal process data that is collected? Answering these questions helps to inform the software engineering community about the suitability of introducing automated assessment tools into advanced computing and software engineering courses.

The ontology alignment task aims at linking two or more different ontologies from the same domain or different domains. Over the years, many techniques have been proposed for ontology instance alignment, schema alignment, and link discovery. Most of the available approaches require human intervention or work within a specific domain and follow a rule-based and logic-based approach. In this paper, we present an ontology alignment approach using graph embedding with negative sampling that is independent of the domain and does not require any human intervention.

Step-based tutoring systems, in which each step of a student's work is accepted by a computer using special interfaces and provided immediate feedback, are known to be more effective in promoting learning than traditional and more common answer-based tutoring systems, in which only the final (usually numerical) answer is evaluated. Prior work showed that this approach can be highly effective in the domain of linear circuit analysis in teaching topics involving relatively simple solution procedures. Here, we demonstrate a novel application of this approach to more cognitively complex, multi-step procedures used to analyze linear circuits using the superposition and source transformation methods. Both methods require that students interactively edit a circuit diagram repeatedly, interspersed with the writing of relevant equations. Scores on post-tests and student opinions are compared using a blind classroom-based experiment where students are randomly assigned to use either the new system or a commercially published answer-based tutoring system on these topics. Post-test scores are not statistically significantly different but students prefer the step-based system by a margin of 84 to 11% for superposition and 68 to 23% for source transformations.

This Research full paper addresses the challenge of creating an effective course design that has tight alignment between various course components and incorporates appropriate pedagogy and assessment techniques. Many systems have been proposed solely for the purpose of guiding instructors through the process of course design so as to achieve maximum student learning. One such system is the Instructional Module Development System (IMODS). IMODS is a web-based software system that has been developed to assist instructors in curriculum design based on the principles of Outcome-based Education (OBE) and Bloom's Taxonomy. It is not just enough to come up with a model that theoretically facilitates effective result-oriented course design. There should be facts, experiments and proof that any model succeeds in achieving what it aims to achieve. This paper focuses on testing and evaluation of the IMODS platform and deliver feedback to its development team. We present our methodology and instruments used for testing and evaluation of the tool. Data collection and analysis is described and the results of evaluation of IMODS are presented.

To ensure that future generations of engineering, science, and other technological practitioners are equipped with the required knowledge and skills to continue to innovate solutions to solve societal challenges, effective courses or instructional modules that incorporate best pedagogical and assessment practices must be designed and delivered. Science, technology, engineering and mathematics (STEM) educators typically come from STEM backgrounds and have little or no formal STEM education training. Their approaches to learning, instruction, and assessment mimic the experiences they were exposed to as students and are not necessarily informed by scholarship in the area of how people learn. The road to effective STEM instruction starts with a well-conceived and constructed plan or curriculum that includes the tight alignment of content, pedagogical approaches and assessments, around the learning objectives, and draws upon best-practices in each of these areas. An information technology (IT) tool that can guide STEM educators through the complex task of course design development, ensure tight alignment between various components of an instructional module, and provide relevant information about research-based pedagogical and assessment strategies will be of great value. This demonstration presents a Web-based software tool called the Instructional Module Development System (IMODS) that supports these ventures and broadens the impact and reach of professional development in the scholarship of teaching and learning, particularly to STEM faculty.

An information technology (IT) tool that can guide STEM educators through the complex task of course design development, ensure tight alignment between various components of an instructional module, and provide relevant information about research-based pedagogical and assessment strategies will be of great value. A team of researchers is engaged in a User-Centered Design (UCD) approach to develop the Instructional Module Development System (IMODS), i.e., a software program that facilitates course design. In this paper the authors present the high-level design of the IMODS and demonstrate its use in the development of the curriculum for an introductory software engineering course.

The Software Enterprise is a pedagogical model combining traditional lecture with project-based learning. The Enterprise model leads students through a modular series of lessons that combine foundational concepts with skills-based competencies. In this tutorial, software engineering educators in higher education or industry will learn the methodology, get exposed to assessment techniques such as e-portfolios and concept maps, and become familiarized with the open resources available to educators that adopt the pedagogy. This tutorial should be of interest to any educator interested in making their project-based courses more engaging and more relevant to students needing to be ready to practice the profession from the first day they exit the Enterprise environment.

Software engineering education is a technologically challenging, rapidly evolving discipline. Like all STEM educators, software engineering educators are bombarded with a constant stream of new tools and techniques (MOOCs! Active learning! Inverted classrooms!) while under national pressure to produce outstanding STEM graduates. Software engineering educators are also pressured on the discipline side; a constant evolution of technology coupled with a still emerging engineering discipline. As a handson engineering discipline, where engineers not only design but also construct the technology, guidance on the adoption of project-centric curricula is needed. This paper focuses on vertical integration of project experiences in undergraduate software engineering degree programs or course sequences. The Software Enterprise, now in its 9thyear, has grown from an upper-division course sequence to a vertical integration program feature. The Software Enterprise is presented as an implementation of a project spine curricular pattern, and a plan for maturing this model is given.

A well-designed and constructed course plan or curriculum is an integral part of the foundation of effective STEM instruction. This paper presents a framework for outcome-based course design process and its translation into a semantic web-based tool; i.e., the IMOD™ system. This system guides STEM educators through the complex task of curriculum design, ensures tight alignment between various components of a course (i.e., learning objectives, content, assessments, and pedagogy), and provides relevant information about research-based pedagogical and assessment strategies. The theoretical framework is presented, along with descriptions and screenshots of the implementation of key features.

Software engineering (and by extension software engineering education) is a fast-paced and still emerging discipline (by historical comparison to traditional engineering), yet still immature. We argue this immaturity shows in software engineering education in two ways. First, significant efforts in the software engineering and computer science communities focus on content taxonomies or bodies of knowledge (BOKs), whereas BOKs are more established in traditional engineering disciplines. Second, project experiences are not viewed as a central integrating feature of a degree program's curricular implementation. Project experiences tend to be disjoint; there may be a "freshman project" or a "capstone" or an "undergraduate research experience" or merely a semester project undertaken by the individual initiative of an instructor. The Software Enterprise at Arizona State University uses project experiences as the contextual teaching and learning vehicle throughout the Bachelor of Science in Software Engineering degree program. Students engage in classroom learning, group-oriented lab exercises, implementation on scalable projects, and reflective assessment co-located in time for each concept. The result is a student who not only acquires a new skill, but also immediately understands how to put that skill in practice. The Software Enterprise, now in its 9th year, has evolved from an upperclassmen experience to the full-fledged project spine in the Software Engineering program. In a project spine, content is de-emphasized; foundational concepts are tied to project work throughout the undergraduate program. The Enterprise provides over 40 curricular modules (with labs), assessment tools, and pedagogical guidance on project-centered learning to computing educators.

The success and acceptance of Web service composition depends on computing solutions comprised of trustworthy services. In this paper, we extend our Web service Composition framework to include selection and ranking of services based on their reputation score. With the increasing popularity of Web-based Social Networks like Linked in, Facebook, and Twitter, there is great potential in determining the reputation score of a particular service provider using Social Network Analysis. We present a technique to calculate a reputation score per service using centrality measure of Social Networks. We use this score to produce composition solutions that consist of services provided by trust-worthy and reputed providers.

Service-oriented computing (SOC) has emerged as the eminent market environment for sharing and reusing service-centric capabilities. The underpinning for an organization's use of SOC techniques is the ability to discover and compose Web services. Although industry approaches to composition have a strong notion of business processes, these approaches largely use syntactic descriptions. As such composition is limited since the true functionality of ambiguous service operations cannot be inferred. Alternatively, academia uses semantic approaches to disambiguate services, but, at the same time, most of these approaches neglect the process rigor needed for complex compositions. In this paper we present a generalized semantics-based technique for automatic service composition that combines the rigor of process-oriented composition with the descriptiveness of semantics. Our generalized approach extends the common practice of linearly linked services by introducing the use of a conditional directed acyclic graph (DAG) where complex interactions, containing control flow, information flow and pre/post conditions, are effectively represented. Furthermore, the composition can be represented semantically as OWL-S documents. Our contributions are applied for automatic workflow generation in context of the currently important bioinformatics domain.

Service-oriented computing is gaining wider acceptance. For Web services to become practical, an infrastructure needs to be supported that allows users and applications to discover, deploy, compose and synthesize services automatically. For this automation to be effective, formal semantic descriptions of Web services should be available. In this paper we formally define the Web service discovery and composition problem and present an approach for automatic service discovery and composition based on semantic description of Web services. We also report on an implementation of a semantics-based automated service discovery and composition engine that we have developed. This engine employs a multi-step narrowing algorithm and is efficiently implemented using the constraint logic programming technology. The salient features of our engine are its scalability, i.e., its ability to handle very large service repositories, and its extremely efficient processing times for discovery and composition queries. We evaluate our engine for automated discovery and composition on repositories of different sizes and present the results.