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Pattern of classroom activities during students’ use of computers: Relations between instructional strategies and computer applications Fethi A. Inan a, * , Deborah L. Lowther b , Steven M. Ross c , Dan Strahl c a Instructional Technology, Texas Tech University, College of Education, Room #267, Box 41071, Lubbock, TX 79409, USA b The University of Memphis, USA c Center for Research in Educational Policy, The University of Memphis, USA article info Article history: Received 13 November 2007 Received in revised form 2 January 2009 Accepted 16 June 2009 Keywords: Computer uses in education Technology integration Instructional technology Teaching methods Computer-assisted instruction Educational software abstract The purpose of this study was to identify instructional strategies used by teachers to support technology integration. In addition, relations between types of computer applications and teachers’ classroom practices were examined. Data were direct observation results from 143 integration lessons implemented in schools receiving federal technology grants. Results reflect use of student-centered practices such as teacher as a facilitator, project-based learning, and independent inquiry. Furthermore, this study revealed that classroom practices tend to be more student-centered when students use the computer as a learning tool such as the Internet, word processing, and presentation software. Conversely, drill and practice software showed a dissimilar pattern. Ó 2009 Elsevier Ltd. All rights reserved. Technology implementation in schools has been a major focus of educational reform and policies for several decades (Culp, Honey, & Mandinach, 2003; Web-Based Education Commission, 2000). Within the last decade, over $40 billion was spent to place computers in schools and provide Internet connections to each school (CEO Forum, 2001; Dickard, 2003). Consequently, the student-to-Internet-connected computer ratio has improved; today, almost every school has Internet access and about one computer per every four students (Bausell, 2008; National Center for Education Statistics [NCES], 2004). Unfortunately, increased availability of technology in the school has not lead to overall improvement in classroom teaching prac- tices (Cuban, 2001; Cuban, Kirkpatrick, & Peck, 2001; Rutherford, 2004; Windschitl & Sahl, 2002). The computers are rarely used as learning tools, which would not only extend student abilities to solve problems, create products, communicate and share their perspectives with others, but also build 21st Century knowledge and skills (Jonassen, Howland, Marra, & Crismond, 2008; Morrison & Lowther, 2010; Partnership for 21st Century Skills, 2004; Ton- deur, van Braak, & Valcke, 2007). Teachers mainly use computers as delivery tools to present instructional content or to engage students in the use of computer-assisted learning applications such as drill and practice, tutorials, and simulations (Hohlfeld, Ritzhaupt, Barron, & Kemker, 2008; Moursund & Bielefeldt, 1999; O’Dwyer, Russell, & Bebel, 2004; Smeets, 2005). The use of computers as a delivery tool has been the trend for more than a decade, as a 1994 report by Becker (1994) revealed that students at the elementary level used computers extensively to do drills or play educational games rather than as learning tools. An early study by Rakes, Flowers, Casey, and Santana (1999) found that approximately one-third (66.4%) of the 435 teachers surveyed reported that their students used drill and practice type software in the classroom as a regular part of their curriculum, however, 74.7% reported that their students did not use basic desktop publishing software. More recent studies have found that little has changed since Becker’s 1994 findings. A study by Ross, Smith, Alberg, and Lowther (2004), which presented findings from almost 10,000 classroom observations, also revealed that technology was used infrequently as a learning tool, but rather used to deliver instruction such as drill and practice. Relatively few teachers who used computers in their classroom had students use analytic and project-oriented software, but instead, they personally used content delivery tools to support their teaching (Smeets & Mooij, 2001). This type of use is not sufficient to provide students with the essential skills such as critical thinking and problem solving for economic survival in a 21st Century work environment (Casner-Lotto & Barrington, 2006; Dickard, 2002; CEO Forum, 2001). * Corresponding author. E-mail address: [email protected] (F.A. Inan). Contents lists available at ScienceDirect Teaching and Teacher Education journal homepage: www.elsevier.com/locate/tate 0742-051X/$ – see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.tate.2009.06.017 Teaching and Teacher Education 26 (2010) 540–546

Pattern of classroom activities during students’ use of computers: Relations between instructional strategies and computer applications

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lable at ScienceDirect

Teaching and Teacher Education 26 (2010) 540–546

Contents lists avai

Teaching and Teacher Education

journal homepage: www.elsevier .com/locate/ tate

Pattern of classroom activities during students’ use of computers: Relationsbetween instructional strategies and computer applications

Fethi A. Inan a,*, Deborah L. Lowther b, Steven M. Ross c, Dan Strahl c

a Instructional Technology, Texas Tech University, College of Education, Room #267, Box 41071, Lubbock, TX 79409, USAb The University of Memphis, USAc Center for Research in Educational Policy, The University of Memphis, USA

a r t i c l e i n f o

Article history:Received 13 November 2007Received in revised form2 January 2009Accepted 16 June 2009

Keywords:Computer uses in educationTechnology integrationInstructional technologyTeaching methodsComputer-assisted instructionEducational software

* Corresponding author.E-mail address: [email protected] (F.A. Inan).

0742-051X/$ – see front matter � 2009 Elsevier Ltd.doi:10.1016/j.tate.2009.06.017

a b s t r a c t

The purpose of this study was to identify instructional strategies used by teachers to support technologyintegration. In addition, relations between types of computer applications and teachers’ classroompractices were examined. Data were direct observation results from 143 integration lessons implementedin schools receiving federal technology grants. Results reflect use of student-centered practices such asteacher as a facilitator, project-based learning, and independent inquiry. Furthermore, this studyrevealed that classroom practices tend to be more student-centered when students use the computer asa learning tool such as the Internet, word processing, and presentation software. Conversely, drill andpractice software showed a dissimilar pattern.

� 2009 Elsevier Ltd. All rights reserved.

Technology implementation in schools has been a major focus ofeducational reform and policies for several decades (Culp, Honey, &Mandinach, 2003; Web-Based Education Commission, 2000).Within the last decade, over $40 billion was spent to placecomputers in schools and provide Internet connections to eachschool (CEO Forum, 2001; Dickard, 2003). Consequently, thestudent-to-Internet-connected computer ratio has improved;today, almost every school has Internet access and about onecomputer per every four students (Bausell, 2008; National Centerfor Education Statistics [NCES], 2004).

Unfortunately, increased availability of technology in the schoolhas not lead to overall improvement in classroom teaching prac-tices (Cuban, 2001; Cuban, Kirkpatrick, & Peck, 2001; Rutherford,2004; Windschitl & Sahl, 2002). The computers are rarely used aslearning tools, which would not only extend student abilities tosolve problems, create products, communicate and share theirperspectives with others, but also build 21st Century knowledgeand skills (Jonassen, Howland, Marra, & Crismond, 2008; Morrison& Lowther, 2010; Partnership for 21st Century Skills, 2004; Ton-deur, van Braak, & Valcke, 2007). Teachers mainly use computers asdelivery tools to present instructional content or to engagestudents in the use of computer-assisted learning applications such

All rights reserved.

as drill and practice, tutorials, and simulations (Hohlfeld, Ritzhaupt,Barron, & Kemker, 2008; Moursund & Bielefeldt, 1999; O’Dwyer,Russell, & Bebel, 2004; Smeets, 2005).

The use of computers as a delivery tool has been the trend formore than a decade, as a 1994 report by Becker (1994) revealedthat students at the elementary level used computers extensivelyto do drills or play educational games rather than as learningtools. An early study by Rakes, Flowers, Casey, and Santana (1999)found that approximately one-third (66.4%) of the 435 teacherssurveyed reported that their students used drill and practice typesoftware in the classroom as a regular part of their curriculum,however, 74.7% reported that their students did not use basicdesktop publishing software. More recent studies have found thatlittle has changed since Becker’s 1994 findings. A study by Ross,Smith, Alberg, and Lowther (2004), which presented findingsfrom almost 10,000 classroom observations, also revealed thattechnology was used infrequently as a learning tool, but ratherused to deliver instruction such as drill and practice. Relativelyfew teachers who used computers in their classroom hadstudents use analytic and project-oriented software, but instead,they personally used content delivery tools to support theirteaching (Smeets & Mooij, 2001). This type of use is not sufficientto provide students with the essential skills such as criticalthinking and problem solving for economic survival in a 21stCentury work environment (Casner-Lotto & Barrington, 2006;Dickard, 2002; CEO Forum, 2001).

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F.A. Inan et al. / Teaching and Teacher Education 26 (2010) 540–546 541

In contrast to the aforementioned studies, researchers showevidence that use of computers as learning tools can improve thenature of teaching, student learning, and problem solving (Butzin,2001; Grant, Ross, Wang, & Potter, 2005; Kozma, 2003; Lowther,Ross, & Morrison, 2003; Means & Golan, 1998). Unfortunately, asmentioned the use of technology as a learning tool to supportstudent learning in K-12 schools has not been a common teachingpractice (Ertmer, Addison, Lane, Ross, & Woods, 1999; Vannatta &Fordham, 2004). Based on data collected from approximately2156 K-12 teachers, Barron, Kemker, Harmes, and Kalaydjian (2003)found low use of technology to support student productivity,research, or problem solving. Teachers indicated that when thecomputer was used as a learning tool, the primary purpose was tosearch for information or to write papers (Wozney, Venkatesh, &Abrami, 2006). Other studies have found that one of the mostcommonly used software in K-12 settings is word processing due toteacher familiarity with the software, which in turn reduces theneed of technical support (Becker & Ravitz, 2001; Ross & Lowther,2003). Not surprisingly, the Internet is reported as one of the mostcommonly used digital tools in K-12 classrooms (Muir-Herzig,2004; Wozney et al., 2006).

1. Relations between instructional strategies and typeof computer software

Studies related to K-12 technology integration typically providea profile of computer availability, Internet access, and type ofsoftware use. However, the examination of relations betweenteacher pedagogical practices and type of computer applicationgets little attention. In multiple studies, teachers’ pedagogicalorientation and practices toward technology use in the classroomwere differentiated into two broad categories: teacher-centeredand student or learner-centered (Becker, 2000; Ertmer et al., 1999;Niederhauser & Stoddart, 2001). For example, a study byNiederhauser and Stoddart (2001) indicated a significant relation-ship between teachers’ pedagogical perspectives and the type ofsoftware used by the students in the classroom This study showedthat teachers with learner-centered perspectives preferred to havetheir students use ‘‘open-ended software,’’ which allows activestudent participation, production, and construction of knowledgewith tools such as word processing or presentation software. Onthe other hand, teachers with traditional teacher-centered orien-tation leaned toward skilled-based software such as tutorials and/or drill and practice. These findings support those of Becker (2000),which indicated that teachers with constructivist-oriented peda-gogies frequently assign students to use digital learning tools suchas presentation, spreadsheet, and word processing that requireinput and analysis of information.

Although previous studies examined the relation betweenteacher pedagogical orientation and practices and student use ofcomputers, most of these studies relied on self-report data fromteachers. As several researchers point out, teachers usually havesome notion concerning desirable answers, so these types of datamay be unreliable and biased or provide limited and invalidinformation (Hakkarainen et al., 2001; Kopcha & Sullivan, 2007).Furthermore, Hakkarainen et al. (2001) indicated that there is evena discrepancy between teachers’ pedagogical perspectives and theirreported classroom practices. Ertmer, Gopalakrishnan, and Ross(2001) suggest that researchers should focus on what teachers aredoing in terms of beliefs and practices regarding computer use inthe classrooms. Therefore, it is important to observe and recordtype of computer software and how and to what extent theseapplications are used in actual classroom settings. This studyexamined the pattern between types of computer applications andclassroom practices based on realistic data gathered by direct

classroom observations. Specifically, the following researchquestions were addressed:

- What type of classroom orientation, instructional strategies,and student computer activities are conducted in technology-integrated classrooms?

- Is there any common pattern between types of computeractivities (production software, Internet and research software,and educational software) and classroom practices (classroomorientation, instructional strategies, and student activities)?

2. Method

2.1. Participants

The 39 participating schools were located in Tennessee and hadreceived federal funding from the US Department of Education toimplement school-wide technology initiatives. Thirteen of theschools had received Title II Part D (EdTech) funding from the NoChild Left Behind Act and 26 received funding from the TechnologyLiteracy Challenge Fund (TLCF). Both grants required whole-schoolprofessional development under the guidance of a full time tech-nology coach. The data from this study were collected from 143classroom observations of full (45–60-min) pre-scheduled tech-nology integration lessons at both EdTech (N ¼ 39) and TLCF(N ¼ 104) schools.

2.2. Data collection instruments

Two instruments were used to descriptively, not judgmentallyrecord observed classroom practices: the School ObservationMeasure (SOM�) (Ross, Smith, & Alberg, 1999) and the Survey ofComputer Use (SCU�) (Lowther & Ross, 2000). Both instrumentshad been shown to be reliable and valid (Lewis, Ross, & Alberg,1999; Lowther & Ross, 1999; Lowther et al., 2003; Ross et al., 2004;Sterbinsky & Burke, 2004). In addition, trained, unbiased siteresearchers conducted all data collection procedures.

2.2.1. SOMThe SOM was developed to determine the extent to which

different common and alternative teaching practices are usedthroughout an entire school or in a targeted 1-hour lesson (Rosset al., 1999). The observer examines classroom events and activitiesdescriptively, not judgmentally. Notes are taken relative to the useor nonuse of 24 target strategies. The target strategies include bothtraditional practices (e.g., direct instruction, independent seatwork,and technology for instructional delivery) and alternative,predominately student-centered methods associated with educa-tional reforms (e.g., cooperative learning, project-based learning,inquiry, discussion, using technology as a learning tool). An inter-rater reliability study of SOM with trained observers was conductedby Lewis et al. (1999). The study indicated that pairs of observersselected the identical response on the five-category rubric on 67%of the observation form items. Agreement within one categoryoccurs 93.8 of the time and within two categories 100% of the time.A more recent reliability study (Sterbinsky & Burke, 2004) foundsimilar results in that observer ratings were within one category for96% of the whole-school observations and for 91% of the targetedobservations.

2.2.2. SCUThe SCU is a companion instrument to the SOM and was also

used during the targeted observations (Lowther & Ross, 1999). TheSCU was designed exclusively to capture student access to, abilitywith, and use of computers, rather than teacher use of technology.

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Table 1Frequency of student computer activities (N ¼ 143).

NO (%) R (%) O (%) F (%) E (%)

Production software used by studentsWord processing 77.9 5.0 2.9 5.0 9.3Database 97.1 0.7 2.2 0.0 0.0Spreadsheet 90.7 1.4 0.0 2.9 5.0Draw/paint/graphics/photo-imaging 88.6 0.0 3.6 2.1 5.7Presentation 78.7 2.8 4.3 5.7 8.5Authoring 100 0.0 0.0 0.0 0.0Concept mapping 95.7 0.7 0.0 0.0 3.6Planning 99.3 0.0 0.7 0.0 0.0

Internet/research software used by studentsInternet browser 40.1 3.5 2.8 12.0 41.5CD reference 93.6 2.1 2.1 0.7 1.4Communications 97.8 1.4 0.0 0.0 0.7

Educational software used by studentsDrill/practice/tutorial 78.6 2.9 6.4 4.3 7.9Problem-solving 94.9 1.4 0.0 2.2 1.4Process software 97.1 0.7 0.7 0.0 1.4

NO ¼ Not Observed, R ¼ Rarely, O ¼ Occasionally, F ¼ Frequently, E ¼ Extensively.

F.A. Inan et al. / Teaching and Teacher Education 26 (2010) 540–546542

Observers record computer activities by the software beingused. The computer activities are divided into three categoriesbased on the type of software used: (a) production software (wordprocessing, databases, spreadsheets, draw-paint graphics, presen-tation, authoring, concept mapping, and planning), (b) Internet orresearch software (Internet browser, CD reference materials, andcommunications), and (c) educational software (drill-practice-tutorial, problem solving, and process software). Early interraterreliability of SCU was determined in a study that involved pairs oftrained observers who conducted observations in 42 targeted visitsto classrooms that were scheduled to have students utilizingtechnology. Results from the study revealed that overall, the pairedobservers selected the identical SCU response on 86% of the items,with all other responses being only one rating apart (Lowther &Ross, 1999). A more recent reliability study for the SCU (Sterbinsky& Burke, 2004) show that observer ratings were within one cate-gory for 91% of the targeted observations.

2.3. Procedures

In this study, the SOM and SCU was used during targetedobservations to explore classroom practices in prearranged 1-hoursessions in which the teachers were asked to integrate technology.Observed strategies and student computer activities were recordedon SOM and SCU Notes forms that represented 15 minutes ofobserved time. At the conclusion of the visit, the observersummarized, on data summary forms, the frequency with whicheach of the strategies and the computer activities /and softwarewere observed. The frequency for both instruments was recordedusing a five-point rubric that ranges from (0) Not Observed to (4)Extensively observed. To ensure the reliability of data, observersparticipated in a comprehensive training session. An observer’smanual provided definition of terms, examples and explanations ofthe target strategies, and a description of procedures forcompleting the instrument. After the training session, eachobserver also participated in sufficient practice exercises in realclassroom settings to ensure that his/her data were comparablewith those of experienced observers.

Observation data from TLCF and EdTech schools were collectedby trained observers and both SOM and SCU were used during theobservations. Four targeted observations for each of the 26 TLCFschools and three-targeted observation for each of the 13 EdTechschools were conducted. Teachers from each grant school wererandomly selected and informed prior to the observation todemonstrate a prepared lesson using technology. Observersworked with the teachers, technology coaches, and administratorsto schedule all data collection events.

2.4. Data analysis

Observation data were analyzed by descriptive statistical tech-niques including frequencies, percentages, means and standarddeviations. Furthermore, two-way contingency table analyses(chi-square for independence) were conducted to determine ifrelationships existed between the four most commonly used soft-ware applications and the 17 most frequently observed instruc-tional strategies. The most commonly used software applicationswere Internet browser, word processing, drill and practice, andpresentation. The instructional strategies consisted of four orien-tations (direct instruction, team teaching, cooperative learning, andindividual tutoring), six instructional strategies (higher-levelinstructional feedback, integration of subject areas, project-basedlearning, use of higher-level questioning strategies, teacher actingas a coach/facilitator, parent/community involvement in learningactivities), and seven student activities (independent seatwork,

experiential/hands-on learning, systematic individual instruction,sustained writing/composition, sustained reading, independentinquiry/research on the part of students, student discussion). Eachof the variables was coded as not observed (rubric category ¼ 0)and observed (categories 1–4 combined). Results did not includeanalyses that had an expected count of less than five (Huck, 2008;Sheskin, 2000).

3. Results

3.1. Student computer activities

SCU results indicate that the students were using a variety ofsoftware applications during classroom observations. Internetbrowser was the most commonly observed application as it wasobserved being used by students rarely to extensively in nearly 60%of the classrooms. In nearly 25% of the classes, other softwareobserved in the range of rarely to extensively were word processing(22.1%), drill/practice/tutorials (21.4%), and presentation (21.3%).Database, concept mapping, communications, and process softwarewere the least observed software, which were being utilized in lessthan 5% of the visits. Authoring software was the only software notobserved. Table 1 depicts the observed student computer activities.

3.2. Instructional strategies

SOM data revealed that the most commonly observed strategiesacross all classes were teacher acting as a coach or facilitator(90.1%), direct instruction (72.7%), use of higher-level questioning(46.8%), cooperative or collaborative learning (46.2), and project-based learning (42.7%). Systematic individual instruction andparent/community involvement in learning activities were onlyobserved in less than 5% of the observations. In the majority of theobservations (85.3%), technology was used as a learning tool orresource more commonly than for instructional delivery (55.2%).Table 2 presents the observed classroom activities.

3.3. Type of software and instructional strategies

The chi-square analysis revealed that word processing, presen-tation and Internet had a significant relationship with student-centered activities. This included collaborative learning, integrationof subject areas, project-based learning, independent inquiry, and

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Table 2Frequencies of instructional strategies used (N ¼ 143).

NO (%) R (%) O (%) F (%) E (%)

Instructional orientationDirect instruction (lecture) 27.3 24.5 13.3 18.2 16.8Team teaching 84.6 1.4 2.8 4.2 7.0Cooperative/collaborative learning 53.8 4.2 9.8 17.5 14.7Individual tutoring 88.8 5.6 4.2 1.4 0.0

Instructional strategiesHigher-level instructional feedback 60.8 12.6 12.6 7.7 6.3Integration of subject areas 72.7 2.1 7.0 9.1 9.1Project-based learning 57.3 2.8 4.2 13.3 22.4Use of higher-level questioning strategies 53.2 15.6 16.3 9.2 5.7Teacher acting as a coach/facilitator 9.9 5.0 14.2 31.2 39.7Parent/community involvement 96.5 0.7 0.7 0.7 1.4

Student activitiesIndependent seatwork 48.3 9.1 7.7 14.7 20.3Experiential, hands-on learning 65.0 2.8 6.3 14.0 11.9Systematic individual instruction 95.8 0.7 1.4 2.1 0.0Sustained writing/composition 83.9 3.5 6.3 3.5 2.8Sustained reading 87.4 5.6 3.5 2.1 1.4Independent inquiry/research 57.0 5.6 9.2 12.0 16.2Student discussion 69.2 9.8 4.9 9.8 6.3

NO ¼ Not Observed, R ¼ Rarely, O ¼ Occasionally, F ¼ Frequently, E ¼ Extensively.

F.A. Inan et al. / Teaching and Teacher Education 26 (2010) 540–546 543

student discussion. Drill and practice applications showeda dissimilar pattern compared to other computer applications.These applications were most commonly used for independentseatwork and instructional delivery. Table 3 summarizes the asso-ciations between software applications and instructional strategies.

4. Discussion

4.1. Student computer use and classroom activities

In terms of the usage of computer applications in the class-rooms, the results showed that although various software appli-cations were being used by the students, the Internet browser wasthe most commonly observed application. Other software observedrarely to extensively, in nearly 25% of the classes, were word pro-cessing, drill and practice, and presentation. Understandably,studies conducted when the Internet was first introduced toschools showed that drill and practice and word processing, ratherthan the Internet, were the most commonly used software(McGraw, Blair, & Ross, 1999; Reichstetter, 2000; Ross & Lowther,2003). However, more recent studies reflect results similar to thisstudy in that they revealed an increased use of Internet (Bennett &Pye, 2003; Grant et al., 2005; Lowther, Strahl, Inan, & Bates, 2007).Researchers suggest that this shift is probably a part of movementaway from traditional drill and practice use of the computer tomore project-oriented student-centered and collaborative activi-ties (Lindstrom & Niederhauser, 2003; Liu, 2004; Niederhauser &Lindstrom, 2006).

In this study, extent of computer application usage was broad;ranging from moderate (60%) to not observed at all. The resultscould possibly be attributed to two main factors: the innate func-tions and attributions of the software and teacher proficiency withthe software. For example, word processing is fundamental towriting reports, essays, and other forms of writing activities that arethe main component of student work for all grade levels and subjectareas. In a related study by Muir-Herzig (2004), the author foundthat students most commonly used word processing and Internetduring classroom activities. They also found that teacher profi-ciency on these two computer applications was similarly very high.

In regard to classroom practices, the results of this studyrevealed that computers were used as a learning tool

(e.g., production and research) rather than used for instructionaldelivery in the majority of observations. In other words, teachersimplemented student-centered strategies more frequently thanteacher-centered strategies. For example, teachers acted as a coachor facilitator rather than lecturer when technology was integratedas a learning tool in the lesson. Moreover, use of higher-levelquestioning, cooperative and project-based learning were observedin almost one-half of the observations. These results contrastprevious studies which showed the computers primarily beingused for instruction delivery (e.g., tutorial or drill and practice)rather than a tool to facilitate student learning and engagement(Lowther et al., 2003; Niederhauser & Lindstrom, 2006; Ross &Lowther, 2003; Smeets & Mooij, 2001).

4.2. Relations between instructional strategies and typeof computer software

As previously mentioned, word processing is one of the mostcommonly used software applications in K-12 because it is easy touse and enables students to create and edit more visually appealingand grammatically accurate products (Morrison & Lowther, 2010;Norton & Sprague, 2001). According to the findings, wordprocessing was found to be positively related to several student-centered activities including cooperative learning, integration ofsubject areas, project-based learning, sustained writing, indepen-dent inquiry and student discussion. Some of the relationships suchas project-based learning, integration of subject areas, andsustained writing can be logically explained. However, the rela-tionship between word processing and collaborative learning andstudent discussion was less obvious. Although word processing istypically considered a way to enhance individual productivity, itcan allow students to work on writing activities in a group (Forcier,1996). These activities can be a result of incorporating collaborativelearning or from the lack of computers in classroom (Kumpulainen& Wray, 1999; Mumtaz & Hammond, 2002). In this study, studentswere observed working at computers in pairs during at least 20% ofthe observations. It is more likely that groups of students usingword processing may work collaboratively to brainstorm ideas orconduct research for a writing project.

The findings revealed that draw/paint/graphics/photo-imagingapplications were positively related with independent seatwork.This is understandable because a student working with or creatinggraphics is more likely to work alone. In a writing activity, two ormore students may discuss a topic and then compose a jointrepresentation of their understanding. On the other hand, thenature of the drawing or editing a photo may not lend itself aseasily to the input of multiple students.

Presentation software was found to be related with threestudent-centered activities: integration of subject areas, project-based learning, and student discussion. This relationship can beexplained by affordance of the software. First, presentations helpstudents to present their ideas or artifacts of project-based learningto other students (Norton & Wiburg, 2003). These presentationscan lead to discussions between students. Second, presentationsoftware (e.g., PowerPoint) can be used as an authoring softwareallowing students to create interactive multimedia products thataddress more than one subject area (Garcia, 2004).

One of the critical elements of today’s classrooms is access to theInternet. Through means of the Internet, students are providedopportunities to search, discover, and utilize information thatmeets individual learning goals (Chen & Paul, 2003; Jonassen, Peck,& Wilson, 1999; Morrison & Lowther, 2010). The current findingsrevealed that there were positive relationships between theInternet and student-centered activities. These activities involvedconducting research, collaboration among students, and the

Page 5: Pattern of classroom activities during students’ use of computers: Relations between instructional strategies and computer applications

Table 3Summary of strategies showing significant association with computer applications.

Word Processing Drawing Presentation Internet Drill

Instructional orientationDirect instruction (lecture)Team teachingCooperative/collaborative learning C C

Individual tutoring

Instructional strategiesHigher-level instructional feedbackIntegration of subject areas CC CC

Project-based learning C CC QUse of higher-level questioning strategiesTeacher acting as a coach/facilitator C

Parent/community involvement in learning

Student activitiesIndependent seatwork C Q CC

Experiential, hands-on learningSystematic individual instructionSustained writing/composition CC

Sustained readingIndependent inquiry/research C CC

Student discussion CC CC

C ¼ Positive and Significant, p < 0.05,; CC ¼ Positive and Significant, p < 0.01; Q ¼ Negative and Significant, p < 0.05.

F.A. Inan et al. / Teaching and Teacher Education 26 (2010) 540–546544

teacher serving as a facilitator. Consequently, independent seat-work was less observed when students used the Internet.

As would be expected, drill and practice or tutorial applicationswere used for instructional delivery of subject matter content andpractice exercises. While research has shown positive results ofusing educational software in specific conditions (Reed, 1996; Reed& Spuck, 1996), other findings revealed that these applications canhave some drawbacks and limitations (Forcier, 1996; Solmon &Wiederhorn, 2000). The findings of this study showed that drill andpractice applications had a negative relationship with project-based learning, while exhibiting a positive relationship with inde-pendent seatwork. Drill and practice activities are completedindividually; therefore, they may not allow active studentengagement in the learning process. Moreover, drill and practiceactivities limit collaboration between students (Morrison & Low-ther, 2010).

5. Conclusion

This study showed that classroom practices tend to be morestudent-centered when technology is integrated into lessons wherestudents use production or research software (e.g., word process-ing, presentation, Internet). In contrast, drill and practice applica-tions showed a negative relationship to student-centered activities.By providing data from actual classroom practices, the results ofthis study extended the findings of previous studies (c.f, Becker,2000; Niederhauser & Stoddart, 2001) that demonstrate relationsbetween teachers’ software selection and their pedagogicalperspectives.

Although, this study revealed relationships between the soft-ware and instructional strategies, it did not examine the directionof this relationship. Further studies can investigate whether thecomputer applications lead to use of student-centered strategies orvise versa. This study also did not intend to evaluate the effec-tiveness of computer use but, rather the frequency of each softwareuse. Therefore, future studies should consider the quality ofcomputer use rather than the amount of use. This study could beextended by examining the influence of teacher characteristics(e.g., age, experience) and school characteristics (e.g., technologyavailability, support) on instructional strategies and softwarepreferences (Hew & Brush, 2007). An addition of teachers’ previous

technology training and computer experiences can extend anunderstanding of teacher use of technology (Atkins & Vasu, 2000;Robinson, 2003). Similarly, studies should examine how contextualbarriers influenced instructional practices and teaching strategies(Dexter, Anderson, & Becker, 1999; Zhao & Frank, 2003). Further-more, use of software and instructional strategies may differ withrespect to grade level or subject area of the classroom (Newhouse &Rennie, 2001; Ruthven, Hennessy, & Brindley, 2004). Therefore,further research may account for grade level and subject areas.

Future studies may also employ mixed method research toincorporate quantitative research methods along with qualitativedata (e.g., observation, interviews), as well as data collected fromprincipals’, parents’, and students’ perceptions and experiences(Creswell, 2009; Creswell & Plano Clark, 2007; Tashakkori &Teddlie, 2003). Such rich data would provide useful insights intounderstanding technology integration in K-12 schools (Baylor &Ritchie, 2002; Judson, 2006; Ruthven et al., 2004). The findings ofthis study come from structured observation data (Painter, 2001).There are many advantages of using classroom observation.Well-designed observations can provide sufficient data andevidence on the effective use of technology in the classroom(Hilberg, Waxman, & Tharp, 2004). However, a classroom obser-vation technique presents challenges and limitations with regard togathering valid and reliable data. There are concerns regarding theamount of time for observation and appropriate number of obser-vation needed, observer effect, or reliability of administeredobservation instruments (Dirr, 2006; Volpe, DiPerna, & Hintze,2005). The previously mentioned criticisms and limitations do notnecessarily detract from the value and utility of the observationalmethod (Painter, 2001; Waxman, Hilberg, & Tharp, 2004). Obser-vations can allow researchers to explore the process of teaching ina naturalistic setting, provide information that precisely describesthe status of classroom practices, and identify instructional prob-lems (Fish, 2000; Hilberg et al., 2004). If the limitations areaddressed and data collection instruments and processes arecarefully designed and administered, classroom observation tech-niques have promise as reliable and valid classroom measures ofclassroom practice (Dirr, 2006; Patton, 2002)

Teachers’ pedagogical perspectives and practices appeared toshape the type, amount, and way that technology is utilized in theclassrooms (Ertmer et al., 1999; Niederhauser & Lindstrom, 2006;

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Pajares, 1992; Watson, 2001). Therefore, professional developmentopportunities for both preservice and in-service teachers shouldmainly concentrate on teachers’ pedagogical readiness and beliefsto integrate technology (Ertmer, 2005; Gonzales, Pickett, Hupert, &Martin, 2002; Lowther, Bassoppo-Moyo, & Morrison, 1998; Parr,1999; Yildirim, 2000). However, it is suggested that initiallyteachers will need to acquire primary technology competencies andbasic software skills (Snoeyink & Ertmer, 2002; Zhao & Cziko,2001). Teachers’ computer and software knowledge can help themfigure out the functions and capacity of the technology and howeach particular software application might be beneficial to studentlearning (Becker & Ravitz, 2001; Newhouse & Rennie, 2001;Snoeyink & Ertmer, 2002). After teachers become more familiarwith technology, training should be centered on how the use oftechnology enables them to implement student-centered learning,such as collaborative learning, higher-order questioning, encour-aging student independence, and facilitating/coaching studentlearning (Ertmer, 2005; Rodriguez & Knuth, 2000; Windschitl &Sahl, 2002). Therefore, introducing technology gradually andpromoting teachers’ current practices with continuous support willmore effectively enhance teacher use of technology as a learningtool overtime (Cooley, 2001; Lowther, Ross, Inan, & Strahl, 2006;Snoeyink & Ertmer, 2002; Van Melle, Cimellaro, & Shulha, 2003)

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