Assessing Peer Support and Usabilityof Blogging Technology

Yao Jen ChangDepartment of Electronic Engineering

Chung-Yuan Christian University, Taiwanyjchang@cycu.edu.tw

Chu-Hui ChenInstitute of Education

Chung Yuan Christian UniversityChung-Li, Taiwan 320chchen@cycu.edu.tw

OutlineMotivations and backgroundsResearch MethodsExperiment SettingsExperimental Results and ObservationsConcluding RemarksQ&A

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MotivationsExisting base of knowledge on educational

blogging is insufficient.Enthusiastic claims for blogging in educational

settings need to be focused on a comprehensive research base.

Research base should be broadly supported by vigorous empirical studies conducted in the framework of educational theory.

To provide an evidence base for educators who are considering deploying blogs as learning tools

Research QuestionsTo what extent can blogs serve as a tool to

encourage participation and support peer learning in higher education?

Are blogs suited for all students in educational settings, considering their perceivable differences in levels of academic performance and learning preferences?

ApproachesA comprehensive set of research methods,

such as survey, dataset analysis, ethnographical observations, and evidence investigation.

Triangulation of methods was expected to generate more reliable results than use of one single method in a study.

Experiment SettingsCourses: two undergraduate laboratory classes,

namely Java Programming Language and Programming for Web-based Applications

Time: Spring semester of 2005, Fall semester of 2005

Members: 30~40 students Activities: students writing comments to each

other, up to 3 comments per studentStyle: hybrid learning.

Use of blogs to augment the scope of learning, not to replace classroom learning

Triangulation Strategy in EvaluationsGoal

investigation of peer support and social learning data sources

questionnaires for user survey, blog dataset recorded by the system, classroom observations, descriptive online feedback from students, and informal face-to-face conversations with students.

MethodsContent AnalysisSurveyEthnographic observations

The triangulation strategy for the use of multiple methods and data sources has produced a reliable evidence base for this study.

Content Analysisthree attributes of messages mediated through

social software ( as suggested in the work of Hall and Davison)reflection, propositional stances, and affective tones.

All the comments were evaluated on the three dimensions and coded accordingly.

For example, a disagreeing reply with reflective thoughts and positive tones will be coded as RDP, which stands for “Reflective, Disagree, and Positive” in terms of reflection, stances, and tones.

Content Analysis was performed manually.

The first semester had a dominant number of non-reflective comments (61%) while the second semester had the dominance transferred to reflective comments (79%).

The patterns of distributions in propositional stances and affective tone of both semesters showed significant similarity.

Peer support in terms of propositional stances or affection was significant.

Observations through Content Analysis (1/3)

Regardless of the level of reflection, we saw comments in blogs were mostly affectively positive, ranging 54%~81% in our study, showed few negative attitudes, ranging from 2%~9%.

Observations through Content Analysis (2/3)

There is significantly more observed reflection (79%) in the second semester than in the first (34%).

The difference of level of peer support in terms of propositional stances and affective tones remains statistically insignificant over time.

Stances and tones have a strong interaction.

Observations through Content Analysis (3/3)

Usability StudyGoal: to examine the relationship between

students’ academic achievements and perceived usability with blogs

Method: user survey on blog preference cross checked with academic performance

Hypothesis: Students of different levels of academic achievements show differences in learning preferences.

Tool: A chi-square test for independence evaluates statistically significant differences.

Statistical Results

Based on the data analysis, it is found that the hypothesis is supported with χ2 = 6.156, df=2, p<0.05.

This yields a statistically significant difference in student academic achievement versus learning preferences.

We see that higher-achieving students prefer to blogs

DiscussionsLower-achieving students had an especially

difficult time composing a comprehensive work on their blogs. their lower abilities to organize the learning

tasks The higher achieving students showed their

talents in making blogs appealing able to freely have themselves expressed in the

styles

Concluding remarksThe social value of peer support is vastly

supported in the empirical content analysis. Investigation of the usability of blogs for

students with different achievement levels shows differences in blog preferences.

Students with higher academic performance prefer to blogs for assignments, while students with lower academic performance prefer to traditional reports.