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  1. Programs
  3. Computer Science

Computer Science

Arkansas Tech University

Bachelor's Degree

Become a contributor for free to openly demonstrate student outcomes, industry alignment & eligibility criteria.

The Bachelor of Science in Computer Science with an Artificial Intelligence focus provides students with a strong foundation in computing principles, mathematical reasoning, and software development, with specialized study in intelligent systems. The program emphasizes problem solving, algorithmic thinking, and the development of data-driven and adaptive software solutions. The curriculum integrates core computer science theory and practice with applied study in artificial intelligence.

Credits

120 credits

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Program Pathways

Credentials this program stacks toward

No program pathways.

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Program Details

Detailed information about this program

No detailed information available.

Requirements

What you need to earn this credential

No requirements listed.

Financial Aid

Eligible funding programs

No funding information available.

Scholarships

No scholarships listed.

Visit Program Website
Locations

Where this program is offered

  • Russellville, Arkansas

    Administration Bldg 200, 1509 N Boulder Ave, Russellville, Arkansas, 72801-2222

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Related Programs

Programs related to this one

No related programs.

Skills & Competencies

Skills developed through this program

Auto-populated·from O*NET via SOC 25-1021.00

Skills

InstructingReading ComprehensionWritingSpeakingActive LearningLearning StrategiesCritical ThinkingActive Listening

Knowledge

Computers and ElectronicsEducation and TrainingEnglish LanguageCustomer and Personal ServiceMathematics

Abilities

Oral ComprehensionOral ExpressionWritten ComprehensionWritten ExpressionDeductive ReasoningInductive ReasoningSpeech ClarityInformation OrderingNear VisionProblem Sensitivity

Tasks

  • Prepare course materials, such as syllabi, homework assignments, and handouts.
  • Compile, administer, and grade examinations or assign this work to others.
  • Prepare and deliver lectures to undergraduate or graduate students on topics such as programming, da

Technology

Web page creation and editing softwareGraphics or photo imaging softwareVideo creation and editing softwareComputer based training softwareData base user interface and query software

Tools

Carousel slide projectorsCompact digital camerasCompact disk CD playersComputer data input scannersComputer laser printersComputer projectorsConference telephonesDesktop computersDigital calculatorsDigital video disk DVD playersDigital video editorsHandheld microphonesHandheld videocamerasInteractive whiteboard controllersInteractive whiteboards

Work Values

AchievementIndependenceWorking ConditionsRecognitionRelationshipsSupport
Career Pathways

Occupations this program prepares you for

Auto-populated·from O*NET + BLS
Occupations matched to this program, with median wage, top wage, growth, and openings
SOCOccupationMethodWageGrowthOpenings
Match confidence: medium25-1021.00Computer Science Teachers, Postsecondarytitle_inference———
What You'll Learn

Key competencies developed through this program

Auto-populated·from NSX Competency Framework

Mastery: proficient (Level 3)(based on Bachelor's Degree)

  • Comprehensive course materials including syllabi, project scaffolding, and assessment instruments — autonomously design and continuously refine for both undergraduate and graduate computer science programs.
  • Advanced lectures on specialized topics such as machine learning, systems architecture, or distributed computing — prepare and deliver with pedagogical sophistication to mixed undergraduate and graduate audiences.
  • Complex student work including research papers, capstone projects, and graduate theses — evaluate rigorously and provide substantive developmental feedback aligned with professional and scholarly standards.
  • Full examination cycles — independently compile, administer, statistically analyze, and use results to inform iterative improvements to course design in a postsecondary CS department.
  • Multiyear student academic records and longitudinal grade data — manage with precision, using institutional data systems to identify patterns and support student success interventions.
  • Curricula and course content across multiple CS courses — systematically evaluate and revise using evidence-based instructional strategies and alignment with accreditation standards such as ABET.
  • Structured advisement and mentorship — provide to undergraduate and graduate students navigating research pathways, internship opportunities, and career trajectories in computing fields.
  • Applied computing tools including object-oriented development environments, database interfaces, and video creation software — integrate purposefully into course delivery to model professional practice.
  • Non-routine pedagogical challenges such as diverse learner needs or rapidly evolving technology topics — diagnose and resolve using adaptive instructional strategies in a live university classroom.
  • Contributions to departmental scholarship — sustain through active participation in peer-reviewed publication, grant development, or applied research projects relevant to computer science education.

Some details on this page are auto-populated from public workforce data sources: O*NET (opens in new tab), BLS (opens in new tab), College Scorecard (opens in new tab), DOL Training Provider Results (opens in new tab), NSX (opens in new tab). Provided in partnership with LER.me Career Intelligence.

Student Outcomes

Performance metrics for this program

Auto-populated·from Scorecard + DOL
Completion Rate
38%
Placement Rate
55%