Wu, D.; Xu, H.; Sun, Y.; Lv, S.: What should we teach? : A human-centered data science graduate curriculum model design for iField schools (2023)
0.01
0.007890998 = product of:
0.015781997 = sum of:
0.015781997 = product of:
0.031563994 = sum of:
0.031563994 = weight(_text_:b in 961) [ClassicSimilarity], result of:
0.031563994 = score(doc=961,freq=2.0), product of:
0.16126883 = queryWeight, product of:
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.045518078 = queryNorm
0.19572285 = fieldWeight in 961, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.0390625 = fieldNorm(doc=961)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- The information schools, also referred to as iField schools, are leaders in data science education. This study aims to develop a data science graduate curriculum model from an information science perspective to support iField schools in developing data science graduate education. In June 2020, information about 96 data science graduate programs from iField schools worldwide was collected and analyzed using a mixed research method based on inductive content analysis. A wide range of data science competencies and skills development and 12 knowledge topics covered by the curriculum were obtained. The humanistic model is further taken as the theoretical and methodological basis for course model construction, and 12 course knowledge topics are reconstructed into 4 course modules, including (a) data-driven methods and techniques; (b) domain knowledge; (c) legal, moral, and ethical aspects of data; and (d) shaping and developing personal traits, and human-centered data science graduate curriculum model is formed. At the end of the study, the wide application prospect of this model is discussed.
