Chapter 4.5
Observation Measures for Determining Attitudes and Competencies Towards
Technology
Renate Schulz-Zander, Michael Pfeifer, & Andreas Voss
Institute for School Development Research (IFS), University of Dortmund, Germany
Abstract
This chapter provides an insight into how observational measures can contribute for determining attitudes and competencies towards Information and Communication Technology. To
get an idea of the capability of observational measures the first part of this chapter outlines
the meaning of observational techniques as a tool of research and explains what is important
when planning an observational study. For a better understanding in this context, several
video- and audio-supported observation techniques are presented, as well as advantages
and challenges of observational techniques in general. The second part of this contribution
focuses on the methodology and on particular findings of ERIC-referenced empirical studies
that researched attitudes and competencies towards IT by using observational techniques.
After reviewing those studies and summarizing their findings, this chapter ends with the conclusions that observational measures as part of a mixed methods research design have the
potential to deliver meaningful, unique data and findings. One of the major findings is that
attitudes and competencies toward IT tend to be positive in most of the reviewed studies.
Keywords: observation measures, data triangulation, non-standardized research, attitudes/
competencies towards IT
1. Introduction
During the past quarter century major investments have been undertaken in most OECD
countries to bring computers into classrooms. As a result of this effort a rapid improvement in
student-computer ratios could be seen (see OECD, 2004; 2006). In most OECD countries
primary as well as secondary schools have access to computers and educational software
applications in their classes or in specially facilitated computer classrooms.
In the United States the No Child Left Behind legislation puts forward the need to continue
these efforts in the IT sector and makes substantial funds available through a performancebased grant program (The White House, 2001). However, the grant program will also shift
emphasis from ensuring access to IT to assessing the impact that technology has on classroom practices and on how much students learn at school (Dirr, 2003).
Until recent years empirical research on the effects of IT on students’ attitudes and competencies could not provide a clear picture about the relationship between IT access and student academic achievement. The research studies show controversial results: For example
the 2006 OECD PISA report on computer attitudes declares an important effect on the extent
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of computer use and student performance in mathematics (OECD, 2006). Reanalysis of
these results by the German PISA group showed that these effects are negligible if these
analyses are controlled for context variables in a longitudinal data analysis approach
(Senkbeil & Wittwer, 2006).
In order to address these controversies, alternative research approaches to determine the
impact of IT on classroom practice and student achievement need to be considered. The
challenge is to assess not only the extent of technology in the classroom but also the appropriate use of technology to facilitate student learning and to relate these observations to student achievement.
One family of approaches is observation techniques. The main advantage of observation
techniques is that research objectives can be studied in their natural field settings (such as
classrooms) and thereby provide a richer understanding of the topic under investigation.
These techniques allow an alignment of classroom observation with the instructional context
and the evaluation goals. According to Dirr (2003) observation protocols – or forms of observation techniques – serve as valuable tools in order to:

Evaluate the effectiveness of a school program.

Assess the performance of a teacher or a school.

Provide feedback to teachers for professional development.

Conduct basic research on classroom practices.
These functions make observation a useful component of educational research. For example, observation protocols can serve as a tool to measure whether the use of IT programs
achieved anticipated changes in teaching practice and how these changes are related to
student performance.
In this chapter we describe different observation techniques, present the rationale for observation techniques, and discuss their unique characteristics as well as advantages and challenges of this research approach. In addition we present examples of how observation techniques can be used to study IT attitudes and competencies and we report a synthesis of findings. We conclude the chapter by discussing how observation research techniques can be
enriched and combined with quantitative research approaches,
2. Observation as an Approach to Researching IT Competencies and Attitudes
In general observation is regarded as a “primary” data assessment technique due to the
closeness to everyday (non-scholarly) techniques in order to acquire information. In comparison to this “naive” kind of observation, the systematic form of observation under controlled
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conditions by means of structured observation criteria. In the following section different types
of classroom observation measurement instruments are introduced and advantages as well
as limitations of these data assessment techniques are discussed.
2.1 Use of Observation Techniques as a Tool of Research
Observation measures in educational research have been used for decades. Substantial
research focusing on tracking classroom management and interactions that occur between
students and teachers has taken place since the 1970s.
Observation measures for determining attitudes and competencies toward technology include a wide range of approaches, e.g. checklists, inventories, time interval ratings, holistic
ratings, narrative descriptions, and logs. Some of these approaches have built on the prior
work of others, but according to Dirr (2003) there is little evidence of any attempt to bring
cohesion to these efforts.
Observation techniques allow a systematic, structured data collection process, using welldesigned observation record forms. Compared with large-scale summative evaluation tools
the main advantage of these techniques is that data are collected in their natural setting,
thereby providing a richer understanding of the subject under investigation. In the instructional educational research context these techniques allow a researcher to view and monitor
processes that lead to student comprehension. The data can be used to explain students’
performance.
Observational studies in general go through several stages. The Center for Development
Information and Evaluation (1996) named a step-by-step list for observational techniques
which can be used to judge quality. These steps are named in logical order of the data collection and analysis process.
Step 1: Determine the unit of instruction being studied
The first step is to decide which unit of instruction is to be studied. This consideration is especially important when the protocol involves third-party observers. Will they observe an entire class period, a segment, an entire day, an entire course or program? Different protocols
are used to observe different units of instruction. Because of resource constraints, the observational approach has to be selective, looking at a few activities, events, or phenomena that
are crucial to the research questions. A good example of this point is the study of Wecker,
Kohnle and Fischer (2007). The research team chose an observation method which focused
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on the activities on the computer screen and the users’ spoken comments regarding those
activities (see 3.2).
Step 2: Select or develop an observation form
Observation record forms help to standardize the observation process and to ensure that all
important items are covered. They also facilitate aggregation of data gathered from various
sites or by various investigators. Closed response categories (yes or no answers; check
boxes) help to minimize observer variation, and improve the quality of data. If the number of
items in a form is limited then the observation process is more managable. One important
question concerning this step is how the prior work form of other scholars can be integrated
into one’s own research questions.
Step 3: Specify a sample
Once the forms are ready, the next step is to decide where the observations will be carried
out and whether it will be based on one or more schools or classrooms. A single site observation may be justified if the class or school can be treated as a typical case or if it is unique.
However, single observations should generally be avoided. As a rule, several schools’ classes are needed to obtain a reasonable understanding of a situation (see Stigler & Gallimore,
2000). In SITES-M2 (Second Information Technology in Education Study - Module 2) for example the countries selected one or more of the primary, lower secondary, or upper secondary levels, with 4 cases for each level (Kozma, 2003). The cases were selected by a national
panel for their “innovativeness” and for what could be learned from them about how technology is being used to support educational change.
Step 4: Decide on timing
Timing is a crucial point in the observational process, especially when events are to be observed as they occur. Classes normally follow a fixed sequence. Poor timing can distort findings (see Petko, Waldis, Pauli, & Reusser, 2003). Because most studies observe classes
continuously with at least two observers that record their findings independently on a form
and/or by the help of video-technology (see Schaumburg, 2001), the probability of missing
the key-moments when events occur can be decreased.
Step 5: Conduct the field observation
As previously mentioned, an observation team can provide more comprehensive and reliable
data than a single observer (see Schaumburg, 2001). If many classes are to be observed,
non-experts can be trained as observers, especially if observation forms are clear, straightforward, and mostly close-ended.
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Step 6: Complete forms
The observer should take notes as inconspicuously as possible. The best time for recording
is during observation, however, is not always feasible because it may disturb the situation. In
such cases, recording should take place as soon as possible after observation. For example,
McInerney, Mc Inerney, Lawson, and Jacka (1996) used a procedure where the instructor
also took the role as an observer and recorded his observations in a weekly tutorial diary
(see 3.2).
Step 7: Analyze the data
Observation data from close-ended questions can be analyzed using basic procedures such
as univariate and bivariate statistics. Qualitative observations need to be coded in reference
to specific categories with respect to the research questions. Finding these aspects and arranging them together in a system of codes is an important process. The “cyclical analytical
process” includes viewing, coding, and analyzing the data aimed at transforming the video
images into objective and verifiable information (Jacobs, Kawanaka, & Stigler, 1999). Usually
the coding process is repeated several times because in viewing the videotaped material
new aspects might occur important from the researcher’s perspective (also see Stigler, Gallimore, & Hiebert, 2000; Dirr, 2003; Petko, Waldis, Pauli, & Reusser, 2003; Horsley & Walker,
2003). For the coding itself software such as videograph (www.ipn.uni-kiel.de) or ATLAS.ti
(www.atlasti.com) can be used.
Step 8: Check for reliability and validity
Observation techniques are susceptible to error and bias that can affect reliability and validity. Errors can be minimized by following some of the procedures suggested, such as checking the representativeness of the sample of schools or classes selected; using close-ended,
unambiguous response categories on the observation forms, recording observations promptly, and using teams of observers at each site (see Wecker, Kohnle, & Fischer, 2007).
2.2 Video- and Audio-supported Observation
In the early 20th-century, one can find the roots of present observation approaches. However,
early 20th century approaches are now supported by high-end technical devices. Video was
originally used as a stenographic recording method (Stevens, 1910 cited by Stigler, Gallimore, & Hiebert, 2000). The video supported observation was used more than 40 years ago
for the first time in the context of educational research. Now this research approach receives
much attention (Leinhardt, & McCormick, 1996; Stigler, Gonzales, Kawanaka, Knoll, & Serrano 1999; Aufschnaiter, 2001; Ulewicz & Beatty, 2001; Petko, Waldis, Pauli & Reusser,
2003; Seidel, Prenzel, & Kobarg, 2005). Recording audio data is another observational
method. Depending on the research questions a combined use of videotaping and audio-
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recording can be useful since multiple types of data enable the data to be triangulated and
thereby increase confidence in the conclusions drawn.
A recent approach to recording observational data is to record user activities on a computer
screen (Wecker, Kohnle, & Fischer, 2007). This approach can be adequate, for example, for
investigating students’ competencies while using a computer. Compared to videotaping
teachers’ or students’ behavior, screen recording captures all desktop activities. It can deliver
more data about the individuals in detail due to the separately recorded data on each computer. In contrast to the observation with a single video camera this approach can deliver
data from every single computer and its user(s). For capturing the activities on a computer
screen, software has to be installed like Snapz Pro (MAC) (www.ambrosiasw.com) or Camtasia and SnagIt (PC) (www.techsmith.com). If a microphone is installed near the computer
the software is able to record the subjects’ spoken comments during their activities with the
computer.
The latest approach to gaining data on attitudes is the implementation of Face ReaderSoftware (www.noldus.com). This software automatically recognizes specific properties in
facial images, including the following emotional expressions: happy, sad, angry, surprised,
scared, disgusted, and neutral. The emotions are represented as bar graphs and as a continuous signal. An additional gauge display analyzes how negative or positive the emotion is.
This software is currently not a substitute for a human coder but it might be a good support
for precoding video data in respect of specific aspects. A human coder/researcher can select such precoded video sequences and analyze them more deeply in the context of the
whole video. The classifications made by the Face Reader can be exported to analytical and
database programs for further analyses.
2.3 Advantages and Challenges of Observation Research Techniques
Observational data deliver a much wider spectrum of information, which expands the researcher’s ability to analyze complex human interactions such as those in a classroom setting. When using a video-supported observation approach, the analysis of complex human
interactions can be conducted more easily because the recorded video data can be analyzed
again and again. Through this set of techniques unanticipated ideas and alternative analytic
categories can also be discovered. The same set of video data might provide a focal point for
interdisciplinary collaboration. In addition, data gained from video-supported observation allow the integration of qualitative and quantitative methods of analysis (Stigler, Gallimore, &
Hiebert, 2000).
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When conducting an observation in a classroom there are also challenges (Dirr, 2003). Each
observer approaches the classroom with his or her own experiences and biases. As a result,
two observers may focus on different aspects of the classroom and thus they may record
different phenomena for the same lesson. Also every school environment provides a different
context in which the observations take place. This variation can affect the record-keeping
behaviors of the observers. One or more observers may have an effect on classes e.g., on
the behavior of teachers and students. The observed lessons can vary from the “normal”
situation and thus lead to a falsification of the data. Unless the observers and coders are
given extensive training, reliability among their observed and rated data can be low.
Classroom observations, data recording, and data analysis are very time-consuming. Therefore the researcher has to carefully consider which data are needed with respect to the research questions.
3. A Synthesis of Empirical Research Results
The U.S. No Child Left Behind Act (The White House, 2001) emphasizes that the use of
technology in the classroom can be a tool to improve academic achievement. Such legislation emphasizes the fundamental need to gain more knowledge about how integration of IT
in classrooms can be realized. In this respect research on attitudes and competencies toward IT is a major topic for study. Observation techniques may provide a deeper insight into
learner attitudes, compared to standardized questionnaires.
In the following section we present the results of an ERIC search of studies on attitudes and
competencies toward information technologies that used observational techniques. Our major goal is to provide insight on what kind of observation techniques exist and how they are
implemented in studies. Furthermore we will give examples of findings attained by the use of
observation measures and advantages that accrued compared to other methodological approaches. We will synthesize the findings of these studies to put together a picture of what
we can learn from using observation techniques in understanding teachers’ and students’
attitudes and competencies towards technology.
We followed Whitley’s (1997) approach to locate studies. As a first step we conducted a
computerized search the ERIC database from their inception through abstracts available as
of June 1994. We conducted the search using the term 'comput* and attitud*', in which '*' is a
wild-card character that institutes a search for any word having the designated stem. As a
second step the reference lists of prior literature reviews were examined for relevant sources.
Finally, we searched the reference lists of articles located by the other means.
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The ERIC inquiry results on this issue produced a few results based on the keywords observation/measurement, qualitative research, participant observation, data collection, and social
research. The search also produced a small number of results for the keywords attitudes,
students and observation. The largest number of hits was reached with the keywords computer-capabilities, attitudes, computer use in combination with a second set of keywords
computer attitudes, computer literacy, computer uses in education, that were added to the
search by using OR-operators.
3.1 Review of Researches on Attitudes toward Information Technology
Many studies have used the “traditional” observation-method, conducted by one or two persons who joined the observation group and filled out observation forms. This approach of
investigating attitudes is still quite common although the influence of new observation technologies is continuingly growing. A more elaborate way to gain data on attitudes is to use a
triangulation approach. This means the interpretation of the acquired data through observation methods by involvement of other qualitative data (e.g. interviews) or quantitative data
(e.g. questionnaires) collected in parallel. Several studies used mixed methods in order to
capture the richness, complexity, and interdependence of events, actions, and conditions in
the real classroom. Observation methods were also applied to corroborate interview or survey data. Combining data from more than one source helps to detect possible biases in subjective reports. By using triangulation for the interpretation of data, the probability of getting
objective, reliable and valid results is much higher than simply using a single approach.
In the following the methodology and findings of selected studies that use a triangulation approach will be presented. It should be mentioned that in several studies research on attitudes
is just one aspect of the research goals. In many studies research on attitudes is also combined with research on competencies.
One study carried out by Schulz-Zander and Preussler (2005) at the upper secondary level
used a triangulation approach to evaluate a new state program in North Rhine-Westphalia,
which combined self-regulated learning methods with a problem oriented approach to mathematics Data were gained from principal, teacher and student interviews, a student survey
and classroom observations, conducted by two persons and videorecorded.
Students attitudes towards ICT, cooperation, independent learning, academic, computerrelated and mathematic-related self-efficacy were gathered from questionnaires combined
with interview data. The observations were used to support information gained from these
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data. The triangulated data indicated increased self-regulated learning in general, caused by
the new developed materials and learning arrangements. In addition, the study showed significant gender differences. More male students assessed the digital media as supportive for
their learning processes than female students. Males also preferred ICT for self learning,
and felt mathematics more interesting and better visualized through digital media than females, who preferred traditional media. More females had problems with self-regulated learning or functioning as a tutor. Females felt overly challenged to master the difficulties, especially when they did not collaborate with others. Thus, more support was required from the
teacher. Also, significant gender differences related to the academic, mathematic-related and
computer-related self efficacy were found. Males had a significantly higher self-efficacy than
females. High performaning students (mostly males) coped better with the new concept of
mathematics problem orientation, self-regulation, and ICT use than low performing students
did. The findings indicate a cumulative effect for low performing students (see also Preussler
& Schulz-Zander, 2004).
Schaumburg and Issing (2002) carried out a study with a longitudinal pretest-posttest control
group design to investigate the impact of personal mobile computers in the classroom of a
German grammar school (“Gymnasium”) (see also Schaumburg, 2001; 2002). Subjects covered were mathematics, German, and English as a foreign language. To investigate changes
in teaching strategies and classroom practices, the observational data were collected to confirm data (e.g. attitudes towards ICT, teachers and students role, self efficacy) gained from
teacher and student interviews and student surveys. Researchers observed the same classes (Grade 7, 8, and 9) and the same teachers in lessons with and without laptop use. A
randomly selected sample of lessons of the laptop classes was videotaped over 2 ½ years.
The video-supported observations were conducted by two persons, one who did the videotaping and a second person who simultaneously conducted a non-technical unstructured
observation of what was happening in the class. For each interval of 5 minutes length, two
trained observers recorded the dominant media use and form of instruction. Schaumburg
and Issing combined their observations with interviews of the teachers from their observed
lessons to corroborate the information they would get from their observational data (triangulation).
Using teacher interview data, Schaumburg (2002) identified five types of teachers, based on
their attitudes toward teaching with laptops: type 1 focused on teacher-centered instruction,
type 2 focused on media literacy/ technics, type 3 focused on curricular/ content, type 4 focused on didactics and methods, and type 5 supported a constructivist approach. Teachers
of type 4 and 5 composed the minority.
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Results gained from questionnaires and interviews were confirmed through observations with
respect to increased independence of students’ work during laptop lessons. But, the study
could not confirm increased collaborative classroom activities in the laptop lessons for all
three cohorts, when compared to lessons without laptops. The same was true for the shift
from teacher-centered instruction to student-centered learning through laptop use. The video
analysis showed that the change was less profound than the teacher interviews and student
survey data indicated. The amount of independent student work increased significantly during laptop lessons, but for teamwork, pair work, lectures and teacher-guided discussions no
significantly differences were ascertained. Yet, teachers and students felt that the laptops
were valuable tools for teamwork and facilitated collaboration. With respect to the different
types of teachers, Schaumburg found out that only teachers of type 2, 3 and 4 displayed a
change in their teaching style. Type 2 and 4 increased the group work in their classes. Type
2 teachers exhibited a more effective acquisition of computer compentency. Only type 4
teachers practiced collaboration related to content. Solely type 4 could be identified as having made a substantial change of their teacher roles. These findings should be considered in
the context of the investigated school type which in general is more focusing an teachercentered instruction and independent learning and less on cooperative learning.
Another study using the triangulation approach was conducted by Jaervenoja and Jaervelae
(2005). They came to the conclusion that an observation on its own cannot tell enough about
the students’ attitudes towards a computer-supported inquiry learning setting. The authors
used interviews with the students to support their observational data.
In contrast to the ordinary interpreting-process (see Schaumburg, 2001), Jaervenoja and
Jaervelae used a modified approach. By the help of the Noldus Observer software
(www.noldus.com) they transcribed their video-data as a first step. In a second step they
watched the transcripts again and wrote specific descriptions regarding the students’ emotional and motivational expressions as well as volitional behavior. During the second phase
the researchers were more familiar with the data, and looked again at the videotapes with the
transcriptions they had made during the first phase and wrote specific descriptions of the
students emotional and motivational expressions and their volitional behavior.
The aim of Jaervenoja and Jaervelae was to understand how students describe their emotional experiences and their attitudes in computer-supported collaborative inquiry.
The results show five main sources for student’s attitudes during the computer-supported
inquiry learning. Self- and context-driven emotions were the most frequent sources of emotional experiences but also task-, performance- and social-driven emotions were identified.
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Jaervenoja and Jaervelae conclude that these results are in accordance with the idea that
individuals bring their prior learning experiences and assumptions to the learning situation
(Higgins, 1990; Salonen, Lehtinen, & Olkinuora, 1998).
3.2 Review of Research on Competencies for Information Technology
In this section we will give an overview of ERIC-referenced articles concerning the research
on competencies for information technology.
The study of Schaumburg and Issing (2002) and the study of Haeuptle and Reinmann
(2006),both were the same in design (multi-methodological approach), data interpretation
(triangulation) and medium of intervention (notebook computer). The study of Haeuptle and
Reinmann (2006), is also a case study, carried out at a German secondary general school
(“Hauptschule”) in Grades 7 to 10. One of their research questions aimed at clarifying how
the implementation of notebook computers into classes in a school can contribute to improvement of student competencies. In their study they used the observation approach to
support the information that they received from student interviews. Especially when trying to
gather information about competencies the observational approach can deliver data to make
visible processes of acting and reacting. The study comes to the conclusion that the implementation of notebooks into the classroom improves the student IT and social competencies.
The students also developed different strategies in working with and using the notebooks.
Furthermore the students showed their willingness to learn more about ICT.
The purpose of the study of Ilomaeki and Rantanen (2007) was to examine the development
of students’ high-level computer skills and compentency (student expertise) in information
and communication technology (ICT). Design (multi-methodological approaches), data interpretation (triangulation) and also the medium of intervention (notebook computers) were the
same as in the previously presented study. In combination with other methods, classroom
observation was used in this study to describe the classroom activities concerning ICT and
student participation in them. This study used a longitudinal design. Data collection (e.g. observational data, questionnaires) was repeated several times, mostly with a duration of at
least one year in between. Through this approach it became possible to see changes happening over a longer period, e.g. in the students’ ICT compentency caused by the implementation of notebook computers.
Similar to the results of Haeuptle and Reinmann (2006), Ilomaeki and Rantanen also came to
the conclusion that student ICT compentency increased through the use of notebooks in the
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classroom. But in addition they identified differences in the students’ degree and type of ICT
compentency during their three-years of research. They identified a sub-group of students
with a special technical interest in ICT but also a sub-group that used ICT as a tool for their
own creativity and human interests. Ilomaeki and Rantanen also came to the conclusion that
the degree of student ICT compentency depended on the students’ personal interest and
motivation – for instance the time the individual student spent using the internet at home.
McInerney, Mc Inerney, Lawson and Jacka (1996) conducted research on the question of
how a cooperative group setting influences a student’s computer compentency training, in
comparison to a direct instruction setting. The instructor, who was teaching both groups, also
was the observer who provided observational data. After the lessons the instructor recorded
his observational findings in a weekly tutorial diary, which contained several categories of
interest. This tutorial diary was analyzed in a qualitative/intuitive way. Findings were supported by student interviews (triangulation). The study came to the conclusion that an instructional setting that boosts the development of self-regulation and peer-support reduces the
students’ anxiety and increases his or her motivation by enhancing a sense of control and
compentency.
Finally we present a technical state-of-the-art observational approach. This research, conducted by Wecker, Kohnle and Fischer (2007), tried to clarify the question of whether higher
computer compentency – more specifically greater procedural computer-related knowledge,
higher familiarity with computers, and higher self-confidence in using a computer – might be
associated with greater acquisition of knowledge. They collected data by using questionnaires in combination with a screen observation. Screen observation means observing all the
activities that occur on the computer screen by using screen capturing-software. Wecker,
Kohnle and Fischer also recorded audio using an integrated microphone in the computer. It
then became possible to interpret what is seen on the screen by combining this data with the
information that the computer users provide by commenting consciously or unconsciously on
their activities. Wecker, Kohnle and Fischer did the transcription/coding of the video/audiodata with the help of the Videograph-software. This technically-supported observation approach provides new and innovative possibilities for conducting nonparticipating observation.
The findings of this study do not indicate significant positive relations between procedural
computer-related knowledge or self-confidence in using the computer and knowledge acquisition. Notably students having a greater familiarity with IT achieved significantly less
knowledge. Wecker, Kohnle and Fischer interpret these findings in the context of the patterns
of media use by different navigation styles adopted by students with high and low familiarity
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with computers. Students with high familiarity with IT exhibited more shallow processing
strategies ("browsing") which were less functional for learning.
4 Conclusions
The use of observational methods has changed during recent decades from non systematic
and, non-technical to a more objective and reliable, technically-supported method. Based on
the review of research on attitudes and competencies of the ERIC database it can be stated
that most studies used other methodological approaches (e.g., questionnaires or interviews)
as well as observations.
For measuring attitudes and competencies the main value of observational measures is added capability for clarifying explorative research questions. Observational methods can deliver
meaningful, unique data. Especially when using observational data in the context of data
triangulation in combination with other methodological approaches (qualitative as well as
quantitative approaches) – as was practiced in all our reviewed studies – observational investigations are able to provide valuable information about the conditions of the natural field
settings, teaching arrangements, classroom activities and the individuals in detail that help to
make an overall interpretation of the results more objective, reliable and valid.
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