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7.4 Analysis and Measure Social Learning                        117
            technologists is different from what computer scientists and artificial intelligence
            researchers call deep learning in the context of machine learning.
              Content interaction is usually measured by content analysis, which is a method
            to analyze the procedures with text (Rourke, Anderson, Garrison, & Archer,2001).
            The text usually includes chats, discussion boards, and log file data. The content
            analysis includes three steps: (1) adopting a coding scheme, (2) coding the text,
            (3) analyzing the results.

            Case 2 Content analysis of a collaborative inquiry learning among four elementary
            schools in China

              Zheng (2017) analyzed the final products of a collaborative inquiry activity. The
            participants are 196 pupils from 4 classes in four elementary schools in China. The
            pupils were randomly assigned to the groups of four or five.
              At first, Zheng (2017) selected the coding scheme proposed by Zhang et al.
            (2011) to analyze the level of knowledge building. The scheme includes scien-
            tificness and complexity, as shown in Table 7.2.
              In order to make sure the coding is credible, two raters coded all the discussion
            text independently. The raters compared the coding, and Zheng calculated the
            inter-rater agreement that achieved 0.91.
              Finally, Zheng (2017) calculated the percent of each knowledge level. The result
            is shown in Table 7.3.
              Regarding scientificness, the result indicated that 0.4% of the discussion tran-
            scripts were prescientific, 1% of them were hybrid, 18.6% of them were basically
            scientific, and 64% of them were scientific. Zheng (2017) concluded that most
            learners had acquired scientific knowledge about tools in daily life.
              In complexity aspect, the result demonstrated that 16% of discourse transcripts
            were unelaborated facts, 67.3% of them were elaborated facts, only 0.9% of them
            were unelaborated explanations, and 15% of them were elaborated explanations.



            Table 7.2 Coding scheme of knowledge building
            Code                           Explanation
            Scientificness  Prescientific    Contains misconception and naive conceptual
                                           framework
                        Hybrid             Contains misconception and some scientific
                                           information
                        Basically scientific  Not precise, but applies the scientific framework
                        Scientific          Consistent with scientific knowledge
            Complexity  Unelaborated facts  Simple statements
                        Elaborated facts   Elaboration on terms, phenomena, etc.
                        Unelaborated       Includes reasons, relationships, or mechanisms
                        explanations
                        Elaborated         Elaborations on reasons, relationships, or
                        explanations       mechanisms
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