Using Twitter as a Diagnostic Teaching and Learning

Assessment Tool Bahar Karaoğlan

#, Cemre Candemir

#, Elif Haytaoğlu

#,

Gül Boztok Algın#, Sercan Demirci

#

#International Computer Institute, Ege University

Izmir, Turkey, 35100

{bahar.karaoglan, cemre.candemir, elif.acar, gul.boztok, sercan.demirci}@ege.edu.tr

Abstract— Higher education students coming from different

regions and schools have different interests and knowledge levels.

These differences can be exploited by teachers to improve the

course efficiency. Knowing beforehand the misconceptions and

the prior knowledge of the students, the teacher can tune the

content of the lecture accordingly. In traditional systems, short

essay, multiple choice or true-false diagnostic quizzes that

include several potential misconceptions related to the targeted

learning, are often practiced for this purpose. This approach

reveals the differences in prior knowledge, misconceptions and

deficiencies in prerequisite skills amongst the students. The

teacher armed with this information can organize both the

content and the structure of his/her teaching more efficiently.

In this paper, we propose using Twitter as a diagnostic

teaching and learning assessment tool. In this scenario the

teacher tweets hashtags related to key concepts or

misconceptions. The comments of the students are retrieved

using Twitter APIs and stored in a local database. The teacher

views and analyzes the retrieved data to tune her/his instruction.

After lecturing, the same hashtags are sent and responses are

collected. Analysis of the data before and after will reveal how

much learning is achieved. Besides, this tool will enable

instructors to provide some hints to students about the topic of

the lecture and engage students more through the use of social

media.

Keywords— twitter, learning assessment, diagnostic assessment,

lecture tuning, microblogging

I. INTRODUCTION

For higher education courses, the engaged students may

have different levels of prior knowledge and also they may

have various interests which may affect their personal learning.

Since students come from diverse regions and schools, their

learning style preferences also may be different. These

differences decrease the chance of success of a teaching

system which is treating unique to all students. In classical

classroom, summative assessments are often used as a

technique to measure the level of student’s learning after the

completion of a unit or a module. While this is a good way of

checking the success of the teaching period, post assessments

occur too late to influence the period itself. Recent studies [1]-

[3], show that regular use of ongoing assessments, with the

aim to improve the course’s efficiency to make it intelligently

cover all level of students, gives brilliant contributions for

student’s learning results.

Diagnostic assessments enable instructors to have

feedback about the student’s knowledge and needs. Tuning

the course content by considering these data will improve the

course efficiency by shortening the already known parts and

by emphasizing the deficiencies and misconceptions. Besides,

pre-assessments are good means to determine how to teach the

planned content according to the student’s learning skills and

interests. This timesaving strategy also provides a means to

compare the pre and post knowledge of the students at the end

of the teaching process. From the student’s perspective,

diagnostic assessments provide a way to have information and

to think about the incoming topic. It makes students to focus

on what the instructors expect them to learn, whilst they create

a learning goal for themselves before instructors assess them

finally with grades [3].

The classical assessments as well as the whole teaching

and learning approaches change with the innovative

technologies. According to [4], with the information

revolution following the changes in communication

technologies, the importance of what an individual knows is

shifted to what an individual knows how to find out.

Connectivist perspective supports this idea by indicating that

the process of learning is enhanced by anything that increases

the connections among students and instructors and online

resources [5]. Therefore, connectivism theory is somehow

aligned with the learning mechanisms using social media [5].

In such learning environments students can have many

communication abilities with other students which may lead

informal learning by information sharing. Actually, the social

media is already one of the daily habits of young pupils, and

they commonly use it to communicate easily with a

widespread user group and to share and gain information,

media and ideas. Twitter and Facebook are amongst the

mostly used microblogging social media environments [6].

Recently, this easily accessible platform is considered as a

good candidate for a stress-free non-threatening sharing

medium for learning assessments. Since new generation

students are tightly connected to social media, this can be an

opportunity to transfer this habit to the process of learning and

teaching in order to enhance the learning process and increase

the engagement of students [5]. This opportunity triggers a

question arisen in the literature: How can these

communication abilities are exploited as a learning

environment? Although there are many studies conducted,

which aspects of the learning can be improved by social media

remains a significant research area [5].

978-1-4799-4205-3/14/$31.00 ©2014 IEEE

According to the recent studies, students prefer using

twitter because of its anonymity, accessibility and

connectivity [7]. Also students report that twitter provides

enhanced learning about the subject, greater enjoyment of the

module, concise and useful communication, timeliness and

greater realism [8]. On the other hand, the students also value

that the accessibilities of the instructors become more

approachable through social media [5].

Moreover, [9] addresses the usage of microblogging to

encourage informal learning. [9] and [10] listed the

functionalities presented by microblogging in the educational

concepts as “asking questions, giving opinions, changing

ideas, sharing resources and reflection”. The instructors have

used these functionalities in a learning environment to draw

the attention of the students on the subject and encourage

them to participate and articulate their own ideas [11].

The functionalities mentioned above may offer more than

being just an informal teaching platform. Some analytic data

can be extracted from the related communications which

contains clues for directing the lecture for increasing the

efficiency of the learning. This data can be exploited to assess

students’ learning level via pre and post-tests which are

conducted on Twitter. Using these pre-tests, the instructor can

tune her/his lecture content by focusing mainly on the

misconcepted and unknown subjects. The pre-tests can be

conducted through sending hashtags before the lecture.

Moreover, the post-tests provide a learning level of the

students. These post-tests can also be employed on the Twitter

using hashtags.

In this study, twitter is proposed as a diagnostic teaching

and learning assessment tool to improve the course efficiency

in higher education. It is hoped that this tool serves (1) the

assessment of learning via pre and post-hashtags (2) the

opportunity for students to have some hints about the

upcoming lecture; (3) a feedback to instructor for tuning the

content of the lecture; (4) motivation of students via using

social media for learning. The sections of the paper are as

follows: in Section 2, a survey of related work is given; in

Section 3, the framework of the developed tool is presented

and finally, in Section 4 we give concluding remarks.

II. RELATED WORK

As the smart phones and tablets become more accessible,

interest in the usage of social media in many different ways

arouse. Because the idea of using social media for educational

purposes goes very well with both in school and lifelong

learning, many researches and experiments are done on the

subject. Here, we will give brief overview of the current use

of Twitter which is a widely used social media by both the

instructors and the students. From the work done in the

literature we can see that twitter

has shifted teaching and learning techniques to

microblogging applications.

has been used as a tool to engage the students

has been used as a tool to improve language learning

and communicative competence

The studies in [9], [10] and [12] mention the use of

microblogging applications in teaching and learning. In [9] the

usage of Twitter on the area of process-oriented learning in

higher education is investigated. The study points out that

microblogging can be used as a new form of communication

in informal learning. The authors of [10] summarized benefits

and drawbacks about Twitter as an educational tool. From the

point view of students, exploiting Twitter for classroom

activities to get helpful information and for instructors posting

lecture notes via Twitter is amongst the benefits of Twitter.

However, some drawbacks of using Twitter are also noted as

that, it is a time consuming task and it has limited number of

characters. In [12] improving the face-to-face lectures using

Twitter is proposed. During lecture presentation with Twitter,

students ask questions by sending tweets. Also additional

lecture material can be added or students share their ideas

using Twitter while presenting the lecture.

Some of the studies in the literature are focused in using

Twitter as a tool to engage the students like [5], [13] and [14].

Twitter is used for communications amongst undergraduate

students and instructor for 12-week course in [5]. These

communications are analyzed and the results of these

evaluations emphasize that the increase in the level of the

usage of Twitter effects the student engagement positively.

Moreover, according to the study the class attendance is not

related with the usage of Twitter. To understand the practices

of scholars’ on the Twitter network is investigated in [13].

One of the findings of this study indicates that students use

twitter to engage in social network make connections with

other. The study in [14] states that Twitter can impact student

grades and engagement. This study has two groups. The first

group used Twitter and the second group did not. The final

grades for the first group were significantly improved

compared to the second group.

In [15]-[18], improving language learning and enhancing

students’ communication skills are referred. In [15], authors

propose an experiment to analyze the benefit of Twitter to

learn a new language. This study shows that Twitter can help

students to make language communication practice instead of

only oral communication in class environment. In addition, it

is implied that Twitter can be used to form collaborative

community for language learners that share their ideas by

using Twitter in [16]. The study in [17] explores how to utilize

Twitter as a teaching method to learn basic history course with

sharing some readings in Twitter. Students follow each other

and discuss about readings using Twitter. With predefined

hashtags, instructor follows discussions of the students about

readings. During the class, verbal discussions are conducted in

detail after one week of the twitter meetings. The study

indicates that the usage of social media can facilitate the

discourse skills of students. The authors in [18] points out that

the usage of Web 2.0 applications can encourage students to

in terms of communication.

Apart from the studies aforementioned, the results of the

survey from [19] report that most of the academicians do not

even use Twitter since they don’t see the means of it in

education. They also expressed the limited character size in

tweets may limit the expression of ideas. A recent surveys

[20], [21] shows that a very small amount of academicians

used Twitter in class. A larger but yet still small amount of

academicians believe that Twitter is a valuable tool for

classroom use.

III. FRAMEWORK

Our study considers using Twitter as a diagnostic teaching

and learning assessment tool. In particular, the aim is to

investigate tuning content of the lecture by using Twitter

before lecturing. On the other hand, by analyzing the tweets, it

can be revealed how much learning is achieved by twitting

before and after the lecture.

In Twitter, the ‘#’ symbol denotes a hashtag. Hashtag is

used to mark a certain keyword or a topic in tweets [22].

Hashtags categorize the tweets and help to find easily as a part

of specific topic in Twitter search. When a hashtag is searched,

every tweet can be accessed including that hashtag. So, as the

first step instructor must define a good hashtag. A good

hashtag must be quiet short, without using too much of the

140 character limit, logical, which makes it easy to remember,

and unique, which keeps it confined to the class only [23]. As

can be seen in Fig. 1, after defining the hashtag(s), related to

the content of the lecture, the instructor tweets them. Also

he/she make sure to tweet the hashtags quite early and remind

all the students that they are going to use that hashtag in their

responses. Students tweet their comments, questions, videos,

web links or images including the hashtag and these tweets are

stored in a local database with the hashtag. The instructor can

evaluate the students’ interests, prior knowledge,

misconceptions and level of knowledge before the lecture and

according to this evaluation; he/she can tune the content of the

lecture. Also, hashtag and related tweets can be used for the

discussions during the session. Such organized discussions

may be helpful for enhancing the students’ knowledge with

different levels. Besides these, learning can be assessed by

twitting the same hashtag after the lecture. The same hashtag

can be sent with short or long delays depending on the

lecturer’s demand.

Fig. 1 Pre-processing for the lecture through sending hashtags related the keynotes and receiving tweets

Students at different ages, from different regions or

graduated from different kind of high-schools have different

knowledge, thoughts and experience. These data are

significant and valuable; so, storing some demographic data in

a database, such as their high school, age, country or region

may be useful for the instructor to estimate the prior

knowledge of the students while tuning the content of the

lecture.

Since all sent hashtags related to topics of the lecture are

stored in the database, the instructor can perform some

analysis such as which hashtags are sent in which topic, how

many hashtag and tweets are sent and replied in each topic by

querying from the database. A sample query output asking for

the complete list of all tweets that were sent before the lecture

about a certain hashtag could be applied similar to the one in

Table 1.

TABLE I

EXAMPLE OUTPUT OF A SAMPLE QUERY

Tweet-id Tweet Twitter

username

Tweet

date

774873xxx

can we use the database of a

#ubi_rulebasedsystems to make a

decision tree?

student1 18.4.2014

673592xxx #ubi_rulebasedsystems why do we start

at the 3rd tile in path smoothing alg.? student2 17.4.2014

635434xxx There is a relationship between artificial

intelligence and #ubi_rulebasedsytems. student3 17.4.2014

495873xxx #ubi_rulebasedsystems consist of a list of

rules student4 16.4.2014

239789xxx we cannot run in parallel the

#ubi_rulebasedsystems student5 16.4.2014

These analyses provide a general perspective to the teacher

about the lecture and the students. Furthermore, it gives an

idea about common misconceptions of students, and that

guides to the instructor to form his/her lecture.

The local database is needed to store some information

mentioned above. The structure of the database is composed

of three tables: (1) student-table, storing students’ information,

(2) tweet-table, storing hashtags and tweet information, (3)

course-table, storing the topic of the course and hashtags

about the topics. Organization of the database is depicted in

Fig. 2.

Fig. 2 Database design for a single course

Full framework for diagnostic teaching and learning

assessment tool is illustrated in Fig. 3 below.

Fig. 3 Framework for diagnostic teaching and learning tool

IV. CONCLUSIONS

Diagnostic assessments are widely used to collect data

about students including their prior knowledge, skills, and

abilities, and also their interests and misconceptions before

lecturing the course. Using this data, instructors become able

to intelligently tune their course content according to the

needs and skills of the targeted students. In this study, one of

the widely used social media tools, Twitter, is used as a

diagnostic teaching and learning assessment tool. With this

tool, the instructors can draw the attention of the students on

the important points and encourage them to participate and to

articulate their own ideas. While they can collect some data

about the pre-knowledge, they can also assess the learning

level of the students by comparing pre and post-hashtags. As

for students, using this tool, learning goals can be constructed

by motivating on what the instructors expect them. Moreover,

students may have an opportunity to express themselves in a

stress-free platform.

For larger classrooms and distance learning programs,

automated clustering of the tweets of a related hashtag may be

performed using text mining techniques. The collected data

may be clustered according to important keywords. With this

clustering mechanism, the instructor may figure out which

subjects are mostly misconcepted or already known or easy to

comprehend. Such a clustering solution is considered as a

future work.

This work, by introducing Twitter as a tool for learning

assessment and diagnostic teaching, relates well with the

objectives of WP4 of SALEIE Project (Project Ref. 225997-

CP-1-2005-1-FR-ERASMUS-TNPP, October 2005 to 2008)

funded by the European Union. The objective of this work

package is to enhance the competitiveness of EIE education

within Europe, especially in relation to modern global

technical challenges.

ACKNOWLEDGMENT

The authors wish to thank the European Commission for

the grant to SALEIE (Strategic Alignment of Electrical and

Information Engineering in European Higher Education

Institutions) Project: 527877-LLP-1-2012-1-UK-ERASMUS-

ENW.

The authors also thank to Lecturer Kaya Oğuz for sharing

his Twitter data.

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