Literature and Inquiry in Computing
Currently catalogued as Systems Integration
Reading, source-finding, and technical writing are now routinely performed with AI assistants that summarize confidently and fabricate citations, so the professional skill in this area has shifted from locating sources alone to locating them, verifying machine-generated work against them, and disclosing assistance honestly. The course keeps its identity as the department's reading-and-writing seminar while making direct search, verification, provenance, and disclosure the literacy it teaches.
Current description → proposed description
This course explores classic and current articles in the fields of computer science, computer information sciences, and information technology. This course provides insights into effective reading and writing techniques in order to understand science and technology. In addition to specific activities focusing on reading and writing, students will select an interesting area of science or technology to investigate as a guided independent study. Useful information sources for science and technology will be explored, and students will be challenged to read widely and well as a foundation for life-long learning. The relationship between a Christian worldview and the development of science and technology is investigated.
This course develops the reading, writing, and inquiry practices that sustain a computing career. Students engage classic and current articles across computer science, computer information sciences, and information technology, learning to separate an author's central claim from the evidence and benchmarks offered for it. Students locate sources themselves in disciplinary indexes and digital libraries, comparing what direct search returns with what an AI assistant returns. Because technical reading and writing are now routinely mediated by such assistants, verification becomes a core literacy: students trace machine-generated summaries and citations back to primary sources, document what they checked, and disclose assistance under a stated departmental norm. A guided independent study lets each student investigate an area of science or technology in depth, including how agentic AI is reshaping practice there, and present findings to specialist and non-specialist audiences. Students are challenged to read widely and well as a foundation for lifelong learning, and to investigate the relationship between a Christian worldview and the development of science and technology, including the accountability an author keeps for work he or she did not write.
What changes
- Direct source discovery taught alongside verification of AI-generated retrieval
- Verification of AI-generated summaries and citations against primary sources
- Explicit disclosure and attribution norms for AI-assisted writing, assessed as a deliverable
- Independent study now examines how agentic AI is reshaping the chosen field
- Christian worldview strand extended to vocation and accountability for AI-assisted work
6 proposed outcomes, mapped to 10 program outcomes
Each outcome below is written to be observable and assessable, and each is mapped to the program learning outcomes for which it produces evidence.
Students will be able to analyze classic and current articles in computer science, computer information sciences, and information technology, differentiating an author's central claim from the evidence, benchmarks, and reported results offered in support of it, judging whether the reported measurements - including benchmark scores reported for AI systems - actually support the conclusion drawn, and identifying the societal consequences that would follow if the claim held.
PLO 4.1: judging whether reported measurements support an author's conclusion is critical analysis of a data-driven outcome, and naming the societal consequences that would follow if the claim held supplies the ethical and societal-impact element the PLO requires. PLO 6.2: weighing benchmark scores reported for AI systems against the conclusion drawn is quantitative and qualitative analysis of AI results used to reach a defensible judgment.
Students will be able to evaluate AI-generated summaries, literature searches, and suggested citations by locating sources directly in disciplinary indexes and digital libraries, tracing each claim and reference to its primary source, and presenting to the seminar a written attribution and disclosure statement, conforming to a stated departmental norm, that identifies which passages were AI-assisted, how each was verified, and which claims did not survive the check.
PLO 6.1: tracing an AI-produced summary or citation back to the underlying source, after finding that source independently, is the act of interpreting and explaining an AI output rather than accepting it. PLO 5.1: presenting a written disclosure statement to the seminar that names which AI-assisted claims failed verification is communication about AI work delivered transparently and with integrity.
Students will be able to construct a written synthesis from a guided independent study of a self-selected area of science or technology that situates the field's development, its current state, the data and evidence practitioners in that field rely on, the ways agentic AI is reshaping practice within it, and the ethical and Christian-worldview questions that development raises.
PLO 3.1: the synthesis must join the field's data and evidence with both the ethical and the Christian-worldview questions its development raises, which is the PLO's required combination of data science, ethics, and theology. PLO 6.1: explaining how agentic AI is reshaping practice in the chosen field, on the evidence practitioners there rely on, is the PLO's fostering of understanding of AI's impact across fields.
Students will be able to articulate the findings of a technical article for a non-specialist audience in writing and in a seminar presentation, stating plainly what is established, what is contested, and what remains uncertain.
PLO 5.3: rendering a technical article for a non-specialist audience is precisely the translation work the PLO describes. PLO 5.1: naming what is contested and what is uncertain, rather than only what is settled, is communicating with integrity in both the written and the spoken form the PLO names.
Students will be able to evaluate how a Christian worldview has shaped, and should shape, the development and adoption of science and technology, the responsibility a Christian author retains for AI-assisted work he or she did not personally write, and their own calling as stewards of these tools in service to neighbor.
PLO 1.1: judging how technology ought to develop and be adopted requires students to draw on biblical teaching, which the CLO makes the standard of evaluation. PLO 1.2: retaining responsibility for work one did not personally write is the accountability and transparency the PLO places at the center of professional practice. PLO 1.3: evaluating their own calling as stewards of these tools in service to neighbor is the vocational judgment the PLO names.
Students will be able to critique their own research and writing process over the term, identifying where AI assistance strengthened the work, where it introduced error, and which practices they will carry into lifelong professional learning, weighed against the standards of honesty and stewardship their Christian vocation sets.
PLO 4.3: the CLO is structured self-reflection on the student's own research and writing process, explicitly weighed against the standards of honesty and stewardship set by Christian vocation, which is the faith-informed framework the PLO requires.
Program outcomes this course reaches
Filled cells are program learning outcomes with at least one supporting course learning outcome in this course. Sparse coverage is expected — no single course carries all eighteen.