Back to search

Virginia Tech

Beyond Curation: A Validation and Classification Infrastructure for an Educational Content Catalog

Abstract

dc:description.abstract

To address the challenge of discovering computer science learning resources, the Smart Learning Content (SLC) catalog is designed to simplify access to the growing body of educational content. As part of the Standards, Protocols, and Learning Infrastructure for Computing Education (SPLICE) research community's efforts, the catalog functions as a centralized platform supporting SPLICE's objectives of improving interoperability, enabling comprehensive data collection, and facilitating data analysis in computer science education. The SLC catalog stands out from previous catalogs with an approach that applies an ontology-based content organization and validation services. Additionally, it serves as a platform where educators can contribute, access, and share a wide range of resources—including slideshows, interactive exercises, programming tasks, and Learning Tools Interoperability (LTI)-integrated content from various learning tools. While the primary goal of the catalog is to disseminate high-quality learning materials, its extensive and varied content requires robust organization and validation mechanisms to ensure educators can efficiently locate and utilize resources. The catalog is designed to further support diverse content types, including both standalone resources and content bundles. For one of our key contributors, OpenDSA—an e-textbook system—we have adopted latest LTI 1.3 standard. This implementation enables the catalog to disseminate content in both LTI 1.1 and LTI 1.3 standards, ensuring compatibility. One key improvement in LTI 1.3 is its security features, incorporating robust authentication methods to ensure stronger protection of sensitive student information. This updated standard enables learning tools to meet the evolving demands of digital education, providing educators and learners with more secure, flexible, and effective resources.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Computer Science & Applications
Department dc:contributor.department
Computer Science and#38; Applications
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2025

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Aina, Adeyemi Babatunde
Chairs dc:contributor.committeechair
  • Shaffer, Clifford A.
  • Edmison, Kenneth Robert
Committee member dc:contributor.committeemember
  • Fox, Edward A.

Subjects

dc:subject × 7

Rights

dc:rights
Statement dc:rights
  • Creative Commons Attribution 4.0 International
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:42437
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/124292

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Aina, Adeyemi Babatunde. Beyond Curation: A Validation and Classification Infrastructure for an Educational Content Catalog. masters thesis, Virginia Tech, 2025. https://hdl.handle.net/10919/124292