Quantifying Qualitative Analyses of Verbal Data: A Practical Guide

T.H., Michelene

doi:10.1207/s15327809jls0603_1

Cited by 1,318 publications

(813 citation statements)

References 24 publications

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“…Several researchers (e.g., Chi, 1997;Rourke & Anderson, 2004) have described which steps they took in developing a CSCL coding scheme (see Table 1). Development starts with identifying the main analysis goal and defining codes that validly represent the construct under analysis.…”

Section: Validity and Reliability In Content Analysismentioning

confidence: 99%

“…The next step involves identifying those communication aspects that typify each code, including segmentation of data. Segmentation is important because the grain-size of data segments needs to be at the same level at which the typifying communication aspects occur (Chi, 1997). Table 1 Steps for the development of a coding scheme 1.…”

Section: Validity and Reliability In Content Analysismentioning

confidence: 99%

“…Theory on negotiation of common ground originated in linguistics (Clark & Brennan, 1991;Clark & Schaefer, 1989) and cognitivism (Bromme, 2000). The linguistic approach describes how negotiation of common ground appears in conversation, whereas the cognitivist approach focuses on the way new knowledge is processed, the role that prior knowledge plays in this process, and how individual perspectives affect this.…”

Section: A Coding Scheme For the Analysis Of Negotiation Of Common Grmentioning

confidence: 99%

“…The main advantage of this approach is that it quickly bridges the difference between theory and codes, in the same way as the formalism does. This strategy, using the same theory for both the design of CSCL and the analysis of its effects, is also described by Chi (1997).…”

Section: Definition Of the Codesmentioning

confidence: 99%

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The analysis of negotiation of common ground in CSCL

Beers

Boshuizen

Kirschner

et al. 2007

Learning and Instruction

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CSCL research has given rise to a plethora of analysis methods, all with specific analysis goals, units of analysis, and for specific types of data (chat, threaded discussions, etc.). This article describes some challenges of CSCL-analysis. The development of an analysis method for negotiation processes in multidisciplinary teams serves as an example of how these challenges occur in practice. Results reveal a number of tensions with regard to establishing reliable coding procedures without compromising validity, such as how to define codes, and rules for applying codes. The discussion offers some guidelines for content analysis of CSCL-data.

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Section: Validity and Reliability In Content Analysismentioning

confidence: 99%

Section: Validity and Reliability In Content Analysismentioning

confidence: 99%

Section: A Coding Scheme For the Analysis Of Negotiation Of Common Grmentioning

confidence: 99%

Section: Definition Of the Codesmentioning

confidence: 99%

See 2 more Smart Citations

The analysis of negotiation of common ground in CSCL

Beers

Boshuizen

Kirschner

et al. 2007

Learning and Instruction

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show abstract

“…En un sentido práctico, el proceso de codificación se desarrolla a partir de un esquema de categorías abstraídas de un constructo teórico, utilizado para interpretar de manera sistemática las acciones cognitivas que constituyen una evidencia observable a partir de las proposiciones generadas por las verbalizaciones de los individuos (Ericsson y Simon, 1993;Chi, 1997). En el caso del proceso de escritura, estas evidencias son clasificadas en categorías definidas en un esquema o modelo de escritura para posteriormente, hacer un análisis de frecuencias que determinan las categorías más relevantes, utilizadas por los participantes.…”

Section: Procedimientounclassified

Aproximación a un modelo de autorregulación en escritura académica a partir del análisis de protocolos

Camacho

Rodríguez

Vargas

2016

folios

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Supporting learning of variable control in a computer-based biology environment: Effects of prompting college students to reflect on their own thinking

Lin

Lehman

1999

J. Res. Sci. Teach.

250

150

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While instruction on control of variables has been shown to be effective, especially when it encourages students to focus explicitly on rules or procedures, little evidence of application to novel problems has been obtained. We hypothesized that prompting students to understand their own learning processes while doing experiments involving control of variables would allow them to activate their repertoire of knowledge and strategies and learn in a way that would enhance transfer of learning. Students were assigned to one of four versions of a computer-based biology simulation learning environment, each employing a different type of prompt: reason justification, rule based, emotion focused, or none (control). Learning in this computer environment, college biology students designed and conducted experiments involving control of variables. Students' ability to solve both contextually similar (near transfer) and contextually dissimilar (far transfer) problems was assessed. The treatment groups performed equally well on contextually similar problems. However, on a contextually dissimilar problem, the reason justification group had significantly higher scores than the other groups. Qualitative data showed that the reason justification prompts directed students' attention to understanding when, why, and how to employ experiment design principles and strategies, and this in turn helped students to transfer their understanding to a novel problem.

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Quantifying Qualitative Analyses of Verbal Data: A Practical Guide

Cited by 1,318 publications

References 24 publications

The analysis of negotiation of common ground in CSCL

The analysis of negotiation of common ground in CSCL

Aproximación a un modelo de autorregulación en escritura académica a partir del análisis de protocolos

Supporting learning of variable control in a computer-based biology environment: Effects of prompting college students to reflect on their own thinking

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