Top 20 Positive Shifts: Learner Group Differences in FANH Data Analytics Curriculum

535 alumni survey responses from a land-grant university were analyzed to differentiate data analytics curriculum needs. Clustering analysis identified two distinct learner groups: younger professionals prioritizing technical proficiency and older professionals emphasizing strategic competencies. The dataset, created by Zhihong Xu and last updated in May 2026, contains text mining results on word usage patterns across curriculum dimensions.

Use Cases

• Analyzing differences in curriculum priorities based on learner demographics and work experience mentioned in the description
• Validating cluster distinctions between learner groups using text mining results on word usage patterns
• Informing the design of differentiated learning pathways, such as technical labs versus strategic modules, based on expressed learner needs

Strengths

• Survey includes 535 alumni respondents, providing a substantive sample size.
• Analysis combines quantitative clustering with qualitative text mining of open-ended responses.
• Dataset is licensed under CC-BY-4.0, allowing for open sharing and reuse.

Limitations

• Row count and specific column definitions are unknown, limiting detailed assessment of the data structure.
• The dataset is very small at 5.5 KB, indicating limited scope and likely summary-level data.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Survey of alumni from a land-grant university, author Zhihong Xu.

Collection Method

Mixed-methods approach using surveys and text mining of open-ended responses.

Freshness

Last updated 2026-05-27 17:36:55; freshness should be verified.