Can You Tell by My Grades That I Am a Blogger?

A Longitudinal Study of the Use of Blogging as a Pedagogical Tool

and Effects on Expected Grades

Tarjei Alvær Heggernes

and Ole Jakob Bergfjord

Department of Business Administration, Western Norway University of Applied Sciences, Bergen, Norway

Keywords: Blogging, Education.

Abstract: From 2009 to 2013 writing blog posts, and commenting on each other’s blog posts, was a mandatory course

requirement for the students of the subject ØMF101 Administrative Informasjonssystemer (Management

Information Systems) at the former Bergen University College (now Western Norway University of Applied

Sciences). We have data from the students’ activity on the blog network, combined with grades and

demographic data. This makes it possible to explore the effects of blogging, and on a higher level, digital

based active learning, has had on the course outcome. The results show that older students are less active

digitally and get lower grades than younger students, even when compared to average grades for the bachelor

program. All other effects are small or non-existent – including the relation between blogging activity and

exam results.

1 INTRODUCTION

The phenomena of blogging emerged in the late

nineties together with the accessibility of the internet

for casual users. Arguably it was identified as a genre

of its own early in the new millennium (Blood, 2000),

and a part of the emerging Web 2.0 (Berners-Lee,

Dimitroyannis, Mallinckrodt, & McKay, 1994). The

ease of use and interactivity made blogging an

interesting topic for research within higher education.

2 LITERATURE REVIEW

2.1 Current Research Topics and

Methods

A literature review conducted in 2010 found two

groups of research: blog usage profile and the effects

of blogging (Sim & Hew, 2010). The group

researching effects of blogging were separated into

two categories: Effects of blogging on performance

outcome and effects of blogging on affective

outcomes. Both categories relied on student’s self-

reporting and/or analysing contents of blogs. Some

studies reported an elevated perceived level of

reflection as a result of both blogging, and reading

other students blog posts (Xie, Ke, & Sharma, 2008),

and in most cases the students perceived that blogging

did support their learning. In the other category most

student self-reported positive attitudes towards

blogging (Ellison & Wu, 2008).

The research we have found on the subject of

blogging in higher education have for the most part

been based on self-reporting from students on their

perceived experience after blogging, for the most part

during one semester ((Ellison & Wu, 2008),(Kiliç &

Gökdas, 2014),(Song & Chan, 2008),(Halic, Lee,

Paulus, & Spence, 2010) to name a few), some

research goes as far as documenting effects over two

semesters (for example (Yang & Chang, 2012) and

(Kuo, Belland, & Kuo, 2017)), but we have not seen

any longitudinal studies on the subject.

There are some studies that test students’

knowledge level before and after a blogging

experience, for example (Papastergiou, Gerodimos,

& Antoniou, 2011). The study showed no significant

increase in the students’ skills in the course taught, in

the case, basketball skills.

In a broader context it is possible to classify blogs

as social media. If we look outside the research of

blogging as a tool for learning, we find a study done

on the effects of using Twitter as a learning tool in

414

Heggernes, T. and Bergfjord, O.

Can You Tell by My Grades That I Am a Blogger? A Longitudinal Study of the Use of Blogging as a Pedagogical Tool and Effects on Expected Grades.

DOI: 10.5220/0009562804140421

In Proceedings of the 12th International Conference on Computer Supported Education (CSEDU 2020) - Volume 2, pages 414-421

ISBN: 978-989-758-417-6

higher education (Junco, Heiberger, & Loken, 2011).

The study looks at both student engagement and

grades, using both an experimental group and a

control group. The conclusions were that the

experimental group, the group using twitter, were

more engaged and got better grades than the control

group. The study lasted one semester, and compared

both acceptance grades, average grades for the

students across all subjects with the grades for the

specific subject where the students used twitter.

2.2 Recommended Frameworks for

Educational Blogging

A framework for student bloggers and educators is

described in (Kerawalla, Minocha, Kirkup, & Conole,

2009). The first part of the framework consists of an

over-arching technological and pedagogical context

for blogging, where it is important to clarify the

relationship with other e-learning tools provided in

the course, discuss functionality of the blogging

software, and how the blogging fits into the

requirements of the course (e.g. is it a course

requirement). The second part of the framework deals

with developing blogging behaviour and skills for

students based on the audience, the blogging

community, comments and the presentation of the

blogs.

The framework is based on interviews of 15

students on master-level online course. For each part

of the framework the researchers have made several

questions adapted from those interviews. For

example, regarding the audience, one question will

be: Who is my audience? For the relationship with

other e-learning tools, one question will be: What will

blogging offer that other tools will not? The

researchers offer the framework to guide and

encourage educators to think about how they best can

use blogging on their course.

Another case study (Farmer, Yue, & Brooks,

2008) presents blogging as a learning tool in a large

cohort university class. Blogging was introduced as a

formative assessment exercise, for 30% of their final

assessment grade they were asked to maintain a blog

for 12 weeks during a semester. Both posting a blog

post, at least once a week on average, and interaction

with other students’ blog were parts of the

requirement. The researchers used a wide range of

data collection methods, from statistics from the blog

network, content analysis of blog posts to online and

paper-based questionnaires.

A dashboard containing blog titles, number of

entries (blog posts), views and number of comments

were available to students during the period they were

blogging. In conclusion the researchers find that there

is promise in using blogging for learning, but also

problem areas in need of improvement. There are also

some recommendations for good practice. Amongst

the advice are: To be clear about the formative

assessment, ensure adequate technical support, build

early interactivity into the experience and making

some of the transition support activities explicit and

easy for students.

There has also been some research on how

blogging should be integrated in higher education

pedagogy. In a study that included both surveys, logs

from the blog platform and content analysis of the

blog posts it was concluded that the three inter-related

factors of frequency, topic resonance and timeliness

determined the effectiveness of moving students

toward a blogging practice (Freeman & Brett, 2012).

Prompted entries were more frequent than

unprompted, prompted topics helped the students

write blog posts, and several students wrote blog

posts in a “catching up manner” before deadlines.

2.3 Blogging, Student Engagement and

Learning Outcomes

Several of the studies above report a positive attitude

amongst students towards blogging. Interactivity

amongst students, and between students and lecturers

is made possible by the comment feature found on

blog posts. There is research suggesting that students

using technology are more engaged in their work as

students, for example students using electronic voting

systems (King & Robinson, 2009) and educational

games (Annetta, Minogue, Holmes, & Cheng, 2009).

Also, studies have found a positive correlation

between the use of social media and college student

engagement (Heiberger & Harper, 2008).

Student engagement can be defined as the amount

of physical and psychological energy that the student

devotes to the academic experience (Astin, 1984).

Later, (Kuh, 2009) have defined engagement as the

time and effort students invest in educational

activities that are empirically linked to desired college

outcomes. College outcomes, or learning/student

outcomes are subject to much uncertainty in the

literature (Allan, 1996), we argue that engagement

and reflection are amongst the desired outcomes, but

for students' good grades must certainly be a desired

outcome as well.

But, are there any empirical links between

blogging as an educational activity and grades as a

desired outcome in higher education?

Can You Tell by My Grades That I Am a Blogger? A Longitudinal Study of the Use of Blogging as a Pedagogical Tool and Effects on

Expected Grades

415

3 RESEARCH QUESTION

During our literature review we have encountered

very little research that explores if it is possible to tie

blogging as an educational activity to better grades in

the course utilizing this activity. Furthermore, the

available research is based on experiences from one

or two semesters, and the research that examines

grades in connection to social media focuses on the

platform Twitter, and not blogging. Our research

focus is the effect blogging might have on grades in

courses where students are academic bloggers. Our

research questions are as follows:

Are there any group of students that experience

higher grades as a result of using blogging as an

educational tool?

Does higher activity on a blog network lead to

higher grades?

4 DATA AND METHODOLOGY

The data used in this analysis is based on a BSc course

in Management Information Systems. Over a period

of 5 years, between 2009 and 2013, blogging was a

mandatory part of the course. This included writing

own blog posts on relevant subjects, but also

commenting on other’s posts.

4.1 Blogging as a Platform for

Learning

Several factors contributed to the decision of using

this learning method in this course. First, one of the

main subjects of the course was information systems.

The blog network in itself is a system, and thus

represented an opportunity for the student to have

hands-on experience as users of a system, in addition

to using the blog network as an example of more

technical aspects of the course, like databases and

application architecture. A forum could also enhance

activity between students, it would have been

possible using the forum functionality in the LMS

Itslearning, but that functionality was considered less

engaging, and would not have made the point about

the application architecture in the same way, hence a

forum was not chosen for student interaction.

Clarifying this relation between the course subject

and blogging answers some of the suggested

questions proposed by the Kerawalla et al-framework

(Kerawalla et al., 2009). The project was heavily also

inspired by activity-based learning, using writing as a

tool for learning, and learning by peer-review (Xie et

al., 2008).

4.2 Blog Technical Setup

The technical installation and maintenance of the blog

network was done, not by the institution’s IT-

department, but by the media department. The

allocated resources at the media department ensured

adequate technical support, an advice suggested by

Farmer et al (Farmer et al., 2008).

Through the system, each student signed up for a

personal Wordpress-blog, and by using Buddypress

the personal blogs were connected in a

community/blog network. That way, the students

would get a feed of each other’s blog posts and

comments. As participating in the blog network was

mandatory, it needed an easy and transparent way to

see if each student had filled the requirements. This

was solved by making a dashboard showing each

student’s number of blog posts and number of

comments. The dashboard was similar to the

dashboard presented by Farmer et al, and the

clarification of role of blogging as a formative

assessment is in accordance to the Kerawalla et al-

framework.

It is also worth mentioning that for this course, the

blog network also was the main LMS (Learning

Management System). All the material for each

lecture was presented within a blog post/update by the

lecturer, including a description of the lecture,

reference or link to relevant literature and articles, and

often an embedded video for using a flipped

classroom-approach in the lecture. This way the

students had one main platform to deal with during

the course. This is in accordance with Kerawalla et

al’s suggested overarching framework where

clarifying the relationship with other e-learning tools

is an element.

4.3 Blog Content and Comments

The students were somewhat free to choose the

subject of their blog posts, if it fell within the theme

of the course. Suggested, or prompted (Freeman &

Brett, 2012) topics (by the lecturer) included

discussing experiences as users of business software,

discussing blogs and other social media supporting

value creation for companies, blogs about the

blogging learning experience, discussing different

themes from the course, making a report from a guest

lecture, or summarizing a chapter from the course

literature. As for the comments there were no

recommended structure for leaving comments, other

CSEDU 2020 - 12th International Conference on Computer Supported Education

416

than the required number. A more formal structure

might have improved the learning and influenced

grades.

The mandatory requirements for the first year of

using the blog network, 2009, were as follow:

 2 blog posts, minimum 200 word

 10 smaller blog posts/sharing an interesting link

with comments on why it is relevant

 40 comments on other student’s blog posts

The lecturer also made a commitment to comment on

all blog posts, thus building early interactivity as per

Farmer et al’s advice. The students reported via a

survey, not included in this paper, that participating

in the blog network led to a better understanding of

the subject, about 90 % answered agree and

somewhat agree on a survey conducted after the

subject was completed. The lecturer subjectively

noticed higher levels of enthusiasm for the course

amongst the students than in the pre-blogging

versions of the course.

The next year, 2010, the requirements were

modified:

 2 blog posts, minimum 200 word

 3 smaller blog posts/sharing an interesting link

with comments on why it is relevant

 10 comments on other student’s blog posts

Apart from these minor adjustments of the

requirements the course remained the same

throughout the period, with the same curriculum, the

same lecturer, and the same evaluation criteria. Also,

the setup and use of the blog network as an

educational tool was in accordance with parts of the

Kerawall et al-framevork, Farmer et al’s advice and

Freeman and Brett’s factors towards effective

educational blogging, which should improve the

potential for desired learning outcomes for the

students from the experience.

5 METHOD

The student numbers varied somewhat from year to

year, between 55 and 96. In total, 394 students

attended the course throughout the period.

We have a complete quantitative overview of the

blogging network activity based on student ID

numbers. Hence, we know that, for instance, student

X made 4 blog posts in total, and wrote 9 comments

to others’ posts. We also know which posts these

comments are replies to – including what student

wrote the original posts. Although not the main topic

of this paper, it is worth noting that this allows us to

perform a network analysis of student activity, for

instance studying which students comment on each

other’s posts.

Also, for this study the contents of the blog posts

and comments have not been analyzed. An idea for a

later study would be to use Natural Language

Processing for further insight into the blogging

experience.

Neither posts nor comments provides perfect

information of true student activity. Reading others’

blog posts could be useful for learning but is not

counted as activity here. Not all posts and comments

are equally important or thoughtful, and it would of

course also be interesting to measure other activities

related to the blog network (number of page views,

total words written, etc.) Finally, time stamps on the

posts and comments could also been useful, for

instance to separate those who are active throughout

the semester from those who fulfill the activity

requirements during a few hectic hours before the

deadline.

As mentioned above, in this data set we have no

qualitative information about the posts/comments.

Partly because of this, we use received comments,

rather than posts, as a variable in the further analysis.

The logic is that extensive and/or particularly relevant

posts tend to attract comments. Other posts, written in

the last minute to fulfill course requirements, and

maybe containing little else than a link to a semi-

relevant web page, will typically not receive

comments.

Hence, for the purpose of this study, we use

number of written comments and number of received

comments as the two variables expressing activity in

the blogging network.

One novel aspect of this study is that we have been

able to merge this data set with administrative data on

the students, in the same manner as (Junco et al.,

2011). This data set includes information for the

admission process (age, gender and average high

school grades), but also information about grades in

this specific course, as well as each student’s average

grade for the degree. We started this project only

when all relevant students had graduated, and hence

have access to average degree grades for all students.

What we are particularly interested in, and have

used as a variable in this study, is the difference

between grades in this course and the average degree

grade. This difference will of course reflect that some

students are particularly good at this subject, whereas

others are better in other subjects. There will also be

some noise – students can be «lucky” or “unlucky”

with the exam and the grading etc. However, in

addition to this, we also believe that this difference

Can You Tell by My Grades That I Am a Blogger? A Longitudinal Study of the Use of Blogging as a Pedagogical Tool and Effects on

Expected Grades

417

says something about the effects of blogging. All

other courses were taught in a fairly similar and

conservative way, with this course being the only one

using educational blogging. If some types of students

systematically perform better or worse in this course

than in other courses, we think that the teaching

methods will be a likely explanation.

In total, this gives us a data set we consider to be

very good, with the following information included:

6 ANALYSIS

A simple correlation analysis is a useful starting point

– the results are shown in the correlation matrix

below:

Table 1: Illustration of data set.

Student#

Course

grade

High

school

grade

average

Degree

grade

average

Difference,

course grade

minus grade

average

Received

comments

Sent

comments Age Gender

1 4 4,68 3,23 0,77 39 17 21 1

2 3 4,32 3,79 -0,79 43 68 21 1

3 4 4,69 3,09 0,91 57 79 22 1

4 2 4,72 2,31 -0,31 34 26 25 1

5 4 4,81 3,71 0,29 39 65 21 1

6 4 4,58 3,91 0,09 39 29 22 0

Table 2: Correlation matrix. N=394.

Course

grade

High

school

grade

average

Degree

grade

average

Difference,

course

grade

minus

grade

average

Received

comments

Sent

comments Age Gender

Course grade 1,000

High school grade

average 0,318 1,000

Degree grade average 0,763 0,103 1,000

Difference, course

grade minus grade

average 0,589 0,340 -0,073 1,000

Received comments -0,005 -0,059 0,005 -0,013 1,000

Sent comments 0,113 -0,006 0,062 0,097 0,670 1,000

Age -0,252 -0,411 -0,155 -0,194 -0,131 -0,135 1,000

Gender(male=0;

female=1) 0,087 0,224 0,072 0,045 -0,036 0,042 -0,021 1,000

CSEDU 2020 - 12th International Conference on Computer Supported Education

418

Some of the results are obvious and require no

further explanation. For instance, students receive

better grades in this course if they had a good grade

average in high school, and there is also a very high

positive correlation between average degree grades

and the grade in this course.

Other correlations are more interesting. Age is

negatively correlated with everything else, both

performance and measures of blogging activity. The

correlation with performance is in line with previous

internal studies. The negative correlation with

blogging activity is not that surprising – one would

hypothesize that younger students at the time were

more familiar with and interested in blogging.

There is a strong positive correlation between

number of sent comments and number of received

comments, confirming our idea that those students

who are active commentators to a large extent are the

same students writing blogposts that attract

comments from others. However, it is interesting and

slightly surprising to note that the correlations

between blogging activity and the different

performance measures seem very small. One would

expect that time spent writing good blogposts

attracting comments as well as commenting on

others’ posts somehow would translate into better

grades.

Next, we performed a simple regression analysis.

The course grade is here the dependent variable,

whereas measures of blogging activity and

demographic variables are independent variables.

Note that from the table above, the variable

“Difference, course grade minus grade average” is

excluded from the regression, as this is a direct

function of two other variables. Also, note that the

regression is based on only 320 observations, as one

variable (or more) is missing for the last 74

observations. Most often, this is the information about

high school grades. As far as we have been able to

observe, the missing data are missing at random, and

should hence not affect out conclusions.

The results are shown in the table below.

Again, it is not surprising to observe a strong

effect from both high school grade average and

degree grade average. What we find slightly

surprising is that none of the other variables seem to

have a significant effect on course grade. Older

students typically have lower grade average from

high school, and also get lower grades throughout

their degree. Thus, when this is accounted for, it

seems reasonable that age does not carry an additional

effect on its own. However, we are surprised that

blogging activity (measured by sent or received

comments) not seems to affect the course grade at all,

after adjusting for these other demographic factors.

One hypothesis could be that while having little

effect for most students, the blogging worked for

those who really focused on it. Hence, we looked

closer at the data for the top 5% measured by

comment activity (n=16, students sending >58

comments). It is of course difficult to conduct

meaningful statistical analysis for such a small sub-

sample, but we were still somewhat surprised to see

that no interesting relationships could be detected.

This group got slightly better grades than the average,

but again, this could be explained by their better high

school grades and average grades. In fact, the most

interesting observation was that this group consisted

of 14 female and just 2 male students.

Table 3: Regression analysis. N=320.

Coefficient Standard error t-Stat P value

High school grade average 0,357 0,129 2,777 0,006**

Grade average 0,783 0,072 10,888 < 0,001***

Received comments -0,001 0,004 -0,367 0,714

Sent comments 0,004 0,003 1,156 0,248

Age 0,027 0,026 1,035 0,301

Gender (male=0; female=1) 0,078 0,084 0,928 0,354

Can You Tell by My Grades That I Am a Blogger? A Longitudinal Study of the Use of Blogging as a Pedagogical Tool and Effects on

Expected Grades

419

7 DISCUSSION AND

CONCLUSION

We expected to see an effect of blogging activity –

mainly because this activity is directly related to the

course objectives, but also through other, more

indirect mechanisms. For instance; the course was

about management information systems (i.e., IT) – a

reasonable expectation would be that students with a

particular interest in this topic would be more active

bloggers, and also get better grades in the course than

expected based on high school grades or average

grades.

However, no such effect can be detected, not even

among the sub-sample of very active bloggers. Our

research questions were:

Are there any group of students that experience

higher grades as a result of using blogging as an

educational tool?

Does higher activity on a blog network lead to

higher grades?

The results show that the answer is no to both

questions.

This is interesting for several reasons. While

previous literature (for instance Farmer et al, 2008)

indicate that blogging is perceived useful by students,

our study suggests that this not necessarily translates

into better «hard» results as measured by course

grades. We believe this is a useful observation

throughout much of the literature on pedagogical

methods – tools that are perceived to be motivational

and effective by students and/or instructors are not

necessarily the same tools that improve learning as

measured by exam results. This does not imply that

tools and methods which “only” improve student (or

teacher!) motivation or perceived learning without

significantly improving grades should be

discouraged. Increased motivation and course

satisfaction are goals on their own, and of course,

experimenting with different methods in different

settings is also valuable on its own. However, a

clearer definition of what qualifies as «successful»

when using new pedagogical tools could probably be

useful.

Another interesting point is how we measure

learning –in this case, how the exam is structured. The

exam type remained unchanged as blogging was

introduced. A possible objection would be that the

exam should be changed to better reflect the methods

used in the course, or that blogging per se not should

be expected to improve exam results when the skill

set required in a traditional written exam probably is

different from the skill set required for (and promoted

by) blogging.

Finally, it is worth reflecting on how different

practices appeal to different groups of students. In our

case, blogging seemed to appeal to younger students

more than older students, and to female students more

than male students. Of course, this could be good or

bad, but nevertheless worth considering and

measuring when possible.

REFERENCES

Allan, J. (1996). Learning outcomes in higher education.

Studies in higher education, 21(1), 93-108.

Annetta, L. A., Minogue, J., Holmes, S. Y., & Cheng, M.-

T. (2009). Investigating the impact of video games on

high school students’ engagement and learning about

genetics. Computers & Education, 53(1), 74-85.

Astin, A. W. (1984). Student involvement: A

developmental theory for higher education. Journal of

college student personnel, 25(4), 297-308.

Berners-Lee, T., Dimitroyannis, D., Mallinckrodt, A. J., &

McKay, S. (1994). World Wide Web. Computers in

Physics, 8(3), 298-299.

Blood, R. (2000). Weblogs: A history and perspective.

Rebecca’s pocket, 7(9), 2000.

Ellison, N., & Wu, Y. (2008). Blogging in the classroom: A

preliminary exploration of student attitudes and impact

on comprehension. Journal of Educational Multimedia

and Hypermedia, 17(1), 99-122.

Farmer, B., Yue, A., & Brooks, C. (2008). Using blogging

for higher order learning in large cohort university

teaching: A case study. Australasian Journal of

Educational Technology, 24(2).

Freeman, W., & Brett, C. (2012). Prompting authentic

blogging practice in an online graduate course.

Computers & Education, 59(3), 1032-1041.

Halic, O., Lee, D., Paulus, T., & Spence, M. (2010). To blog

or not to blog: Student perceptions of blog effectiveness

for learning in a college-level course. The Internet and

Higher Education, 13(4), 206-213.

Heiberger, G., & Harper, R. (2008). Have you Facebooked

Astin lately? Using technology to increase student

involvement. New directions for student services,

2008(124), 19-35.

Junco, R., Heiberger, G., & Loken, E. (2011). The effect of

Twitter on college student engagement and grades.

Journal of Computer Assisted Learning, 27(2), 119-

132.

Kerawalla, L., Minocha, S., Kirkup, G., & Conole, G.

(2009). An empirically grounded framework to guide

blogging in higher education. Journal of Computer

Assisted Learning, 25(1), 31-42.

Kiliç, E., & Gökdas, I. (2014). Learning through Blogging:

Use of Blogs to Enhance the Perceived Learning of Pre-

Service ICT Teachers. Educational Sciences: Theory

and Practice, 14(3), 1169-1177.

King, S. O., & Robinson, C. L. (2009). ‘Pretty Lights’ and

Maths! Increasing student engagement and enhancing

CSEDU 2020 - 12th International Conference on Computer Supported Education

420

learning through the use of electronic voting systems.

Computers & Education, 53(1), 189-199.

Kuh, G. D. (2009). What student affairs professionals need

to know about student engagement. Journal of college

student development, 50(6), 683-706.

Kuo, Y.-C., Belland, B. R., & Kuo, Y.-T. (2017). Learning

through blogging: Students’ perspectives in

collaborative blog-enhanced learning communities.

Journal of Educational Technology & Society, 20(2),

37-50.

Papastergiou, M., Gerodimos, V., & Antoniou, P. (2011).

Multimedia blogging in physical education: Effects on

student knowledge and ICT self-efficacy. Computers &

Education, 57(3), 1998-2010.

Sim, J. W. S., & Hew, K. F. (2010). The use of weblogs in

higher education settings: A review of empirical

research. Educational Research Review, 5(2), 151-163.

doi:10.1016/j.edurev.2010.01.001

Song, H. S., & Chan, Y. M. (2008). Educational blogging:

A Malaysian university students’ perception and

experience. Hello! Where are you in the landscape of

educational technology? Proceedings ascilite

Melbourne 2008.

Xie, Y., Ke, F., & Sharma, P. (2008). The effect of peer

feedback for blogging on college students' reflective

learning processes. The Internet and Higher Education,

11(1), 18-25.

Yang, C., & Chang, Y. S. (2012). Assessing the effects of

interactive blogging on student attitudes towards peer

interaction, learning motivation, and academic

achievements. Journal of Computer Assisted Learning,

28(2), 126-135.

Can You Tell by My Grades That I Am a Blogger? A Longitudinal Study of the Use of Blogging as a Pedagogical Tool and Effects on

Expected Grades

421