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Towards a low-cost universal access cloud framework to assess STEM students

L. F. S Merchante, Carlos M. Vallez, Carrie Szczerbik

TL;DR

The paper tackles the challenge of securely administering STEM assessments in a remote or hybrid setting by designing a cloud-based, scalable framework that mimics an in-person monitored lab. It combines a proctoring tool (Respondus LockDown Browser) with a JupyterHub-based coding environment orchestrated on Kubernetes, and authenticates users via LDAP to ensure secure, user-specific access. The authors demonstrate that this Setup C can reproduce traditional exam conditions with reduced surveillance complexity and IT overhead, while also benefiting students with disabilities through remote access using their own equipment. They provide replication guidance and cost analyses, showing that a $30$-node cluster can support a $2$-hour exam with a $1$-hour setup for under $9$ dollars, highlighting the practical viability and scalability of cloud deployments for online assessment. Overall, the work advocates broader adoption of cloud-enabled, auto-scaled assessment infrastructures in higher education as a resilient and cost-effective alternative to physical computer labs, with applicability to formative assessments and collaborative learning beyond emergency contexts.

Abstract

Government-imposed lockdowns have challenged academic institutions to transition from traditional face-to-face education into hybrid or fully remote learning models. This transition has focused on the technological challenge of guaranteeing the continuity of sound pedagogy and granting safe access to online digital university services. However, a key requisite involves adapting the evaluation process as well. In response to this need, the authors of this paper tailored and implemented a cloud deployment to provide universal access to online summative assessment of university students in a computer programming course that mirrored a traditional in-person monitored computer laboratory under strictly controlled exam conditions. This deployment proved easy to integrate with the university systems and many commercial proctoring tools. This cloud deployment is not only a solution for extraordinary situations; it can also be adapted daily for online collaborative coding assignments, practical lab sessions, formative assessments, and masterclasses where the students connect using their equipment. Connecting from home facilitates access to education for students with physical disabilities. It also allows participation with their students' own adapted equipment in the evaluation processes, simplifying assessment for those with hearing or visual impairments. In addition to these benefits and the evident commitment to the safety rules, this solution has proven cheaper and more flexible than on-premise equivalent installations.

Towards a low-cost universal access cloud framework to assess STEM students

TL;DR

The paper tackles the challenge of securely administering STEM assessments in a remote or hybrid setting by designing a cloud-based, scalable framework that mimics an in-person monitored lab. It combines a proctoring tool (Respondus LockDown Browser) with a JupyterHub-based coding environment orchestrated on Kubernetes, and authenticates users via LDAP to ensure secure, user-specific access. The authors demonstrate that this Setup C can reproduce traditional exam conditions with reduced surveillance complexity and IT overhead, while also benefiting students with disabilities through remote access using their own equipment. They provide replication guidance and cost analyses, showing that a -node cluster can support a -hour exam with a -hour setup for under dollars, highlighting the practical viability and scalability of cloud deployments for online assessment. Overall, the work advocates broader adoption of cloud-enabled, auto-scaled assessment infrastructures in higher education as a resilient and cost-effective alternative to physical computer labs, with applicability to formative assessments and collaborative learning beyond emergency contexts.

Abstract

Government-imposed lockdowns have challenged academic institutions to transition from traditional face-to-face education into hybrid or fully remote learning models. This transition has focused on the technological challenge of guaranteeing the continuity of sound pedagogy and granting safe access to online digital university services. However, a key requisite involves adapting the evaluation process as well. In response to this need, the authors of this paper tailored and implemented a cloud deployment to provide universal access to online summative assessment of university students in a computer programming course that mirrored a traditional in-person monitored computer laboratory under strictly controlled exam conditions. This deployment proved easy to integrate with the university systems and many commercial proctoring tools. This cloud deployment is not only a solution for extraordinary situations; it can also be adapted daily for online collaborative coding assignments, practical lab sessions, formative assessments, and masterclasses where the students connect using their equipment. Connecting from home facilitates access to education for students with physical disabilities. It also allows participation with their students' own adapted equipment in the evaluation processes, simplifying assessment for those with hearing or visual impairments. In addition to these benefits and the evident commitment to the safety rules, this solution has proven cheaper and more flexible than on-premise equivalent installations.
Paper Structure (18 sections, 7 figures, 1 table)

This paper contains 18 sections, 7 figures, 1 table.

Figures (7)

  • Figure 1: Classical Vs. Docker Virtualization
  • Figure 1: Cluster Basics at Kubernetes Cluster Creation Form from Google Cloud Platform
  • Figure 2: Kubernetes Cluster High-level Diagram
  • Figure 2: Node Pools at Kubernetes Cluster Creation Form from Google Cloud Platform
  • Figure 3: Diagram of the Proposed Test
  • ...and 2 more figures