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

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

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

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

    • Teaching and Teacher Education 26 (2010) 540–546 Contents lists available at ScienceDirect Teaching and Teacher Education journal homepage: www.elsevier.com/locate/tatePattern of classroom activities during students’ use of computers: Relationsbetween instructional strategies and computer applicationsFethi A. Inan a, *, Deborah L. Lowther b, Steven M. Ross c, Dan Strahl ca 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, USAa r t i c l e i n f o a b s t r a c tArticle history: The purpose of this study was to identify instructional strategies used by teachers to support technologyReceived 13 November 2007 integration. In addition, relations between types of computer applications and teachers’ classroomReceived in revised form practices were examined. Data were direct observation results from 143 integration lessons implemented2 January 2009 in schools receiving federal technology grants. Results reflect use of student-centered practices such asAccepted 16 June 2009 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 asKeywords: a learning tool such as the Internet, word processing, and presentation software. Conversely, drill andComputer uses in educationTechnology integration practice software showed a dissimilar pattern.Instructional technology Ó 2009 Elsevier Ltd. All rights reserved.Teaching methodsComputer-assisted instructionEducational software Technology implementation in schools has been a major focus of as drill and practice, tutorials, and simulations (Hohlfeld, Ritzhaupt,educational reform and policies for several decades (Culp, Honey, & Barron, & Kemker, 2008; Moursund & Bielefeldt, 1999; O’Dwyer,Mandinach, 2003; Web-Based Education Commission, 2000). Russell, & Bebel, 2004; Smeets, 2005).Within the last decade, over $40 billion was spent to place The use of computers as a delivery tool has been the trend forcomputers in schools and provide Internet connections to each more than a decade, as a 1994 report by Becker (1994) revealedschool (CEO Forum, 2001; Dickard, 2003). Consequently, the that students at the elementary level used computers extensivelystudent-to-Internet-connected computer ratio has improved; to do drills or play educational games rather than as learningtoday, almost every school has Internet access and about one tools. An early study by Rakes, Flowers, Casey, and Santana (1999)computer per every four students (Bausell, 2008; National Center found that approximately one-third (66.4%) of the 435 teachersfor Education Statistics [NCES], 2004). surveyed reported that their students used drill and practice type Unfortunately, increased availability of technology in the school software in the classroom as a regular part of their curriculum,has not lead to overall improvement in classroom teaching prac- however, 74.7% reported that their students did not use basictices (Cuban, 2001; Cuban, Kirkpatrick, & Peck, 2001; Rutherford, desktop publishing software. More recent studies have found that2004; Windschitl & Sahl, 2002). The computers are rarely used as little has changed since Becker’s 1994 findings. A study by Ross,learning tools, which would not only extend student abilities to Smith, Alberg, and Lowther (2004), which presented findingssolve problems, create products, communicate and share their from almost 10,000 classroom observations, also revealed thatperspectives with others, but also build 21st Century knowledge technology was used infrequently as a learning tool, but ratherand skills (Jonassen, Howland, Marra, & Crismond, 2008; Morrison used to deliver instruction such as drill and practice. Relatively& Lowther, 2010; Partnership for 21st Century Skills, 2004; Ton- few teachers who used computers in their classroom haddeur, van Braak, & Valcke, 2007). Teachers mainly use computers as students use analytic and project-oriented software, but instead,delivery tools to present instructional content or to engage they personally used content delivery tools to support theirstudents in the use of computer-assisted learning applications such 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 * Corresponding author. Century work environment (Casner-Lotto & Barrington, 2006; E-mail address: fethi.inan@ttu.edu (F.A. Inan). Dickard, 2002; CEO Forum, 2001).0742-051X/$ – see front matter Ó 2009 Elsevier Ltd. All rights reserved.doi:10.1016/j.tate.2009.06.017
    • F.A. Inan et al. / Teaching and Teacher Education 26 (2010) 540–546 541 In contrast to the aforementioned studies, researchers show classroom observations. Specifically, the following researchevidence that use of computers as learning tools can improve the questions were addressed:nature of teaching, student learning, and problem solving (Butzin,2001; Grant, Ross, Wang, & Potter, 2005; Kozma, 2003; Lowther, - What type of classroom orientation, instructional strategies,Ross, & Morrison, 2003; Means & Golan, 1998). Unfortunately, as and student computer activities are conducted in technology-mentioned the use of technology as a learning tool to support integrated classrooms?student learning in K-12 schools has not been a common teaching - Is there any common pattern between types of computerpractice (Ertmer, Addison, Lane, Ross, & Woods, 1999; Vannatta & activities (production software, Internet and research software,Fordham, 2004). Based on data collected from approximately and educational software) and classroom practices (classroom2156 K-12 teachers, Barron, Kemker, Harmes, and Kalaydjian (2003) orientation, instructional strategies, and student activities)?found low use of technology to support student productivity,research, or problem solving. Teachers indicated that when the 2. Methodcomputer was used as a learning tool, the primary purpose was tosearch for information or to write papers (Wozney, Venkatesh, & 2.1. ParticipantsAbrami, 2006). Other studies have found that one of the mostcommonly used software in K-12 settings is word processing due to The 39 participating schools were located in Tennessee and hadteacher familiarity with the software, which in turn reduces the received federal funding from the US Department of Education toneed of technical support (Becker & Ravitz, 2001; Ross & Lowther, implement school-wide technology initiatives. Thirteen of the2003). Not surprisingly, the Internet is reported as one of the most schools had received Title II Part D (EdTech) funding from the Nocommonly used digital tools in K-12 classrooms (Muir-Herzig, Child Left Behind Act and 26 received funding from the Technology2004; Wozney et al., 2006). Literacy Challenge Fund (TLCF). Both grants required whole-school professional development under the guidance of a full time tech-1. Relations between instructional strategies and type nology coach. The data from this study were collected from 143of computer software classroom observations of full (45–60-min) pre-scheduled tech- nology integration lessons at both EdTech (N ¼ 39) and TLCF Studies related to K-12 technology integration typically provide (N ¼ 104) schools.a profile of computer availability, Internet access, and type ofsoftware use. However, the examination of relations between 2.2. Data collection instrumentsteacher pedagogical practices and type of computer applicationgets little attention. In multiple studies, teachers’ pedagogical Two instruments were used to descriptively, not judgmentallyorientation and practices toward technology use in the classroom record observed classroom practices: the School Observationwere differentiated into two broad categories: teacher-centered Measure (SOMÓ) (Ross, Smith, & Alberg, 1999) and the Survey ofand student or learner-centered (Becker, 2000; Ertmer et al., 1999; Computer Use (SCUÓ) (Lowther & Ross, 2000). Both instrumentsNiederhauser & Stoddart, 2001). For example, a study by had been shown to be reliable and valid (Lewis, Ross, & Alberg,Niederhauser and Stoddart (2001) indicated a significant relation- 1999; Lowther & Ross, 1999; Lowther et al., 2003; Ross et al., 2004;ship between teachers’ pedagogical perspectives and the type of Sterbinsky & Burke, 2004). In addition, trained, unbiased sitesoftware used by the students in the classroom This study showed researchers conducted all data collection procedures.that teachers with learner-centered perspectives preferred to havetheir students use ‘‘open-ended software,’’ which allows active 2.2.1. SOMstudent participation, production, and construction of knowledge The SOM was developed to determine the extent to whichwith tools such as word processing or presentation software. On different common and alternative teaching practices are usedthe other hand, teachers with traditional teacher-centered orien- throughout an entire school or in a targeted 1-hour lesson (Rosstation leaned toward skilled-based software such as tutorials and/ et al., 1999). The observer examines classroom events and activitiesor drill and practice. These findings support those of Becker (2000), descriptively, not judgmentally. Notes are taken relative to the usewhich indicated that teachers with constructivist-oriented peda- or nonuse of 24 target strategies. The target strategies include bothgogies frequently assign students to use digital learning tools such traditional practices (e.g., direct instruction, independent seatwork,as presentation, spreadsheet, and word processing that require and technology for instructional delivery) and alternative,input and analysis of information. predominately student-centered methods associated with educa- Although previous studies examined the relation between tional reforms (e.g., cooperative learning, project-based learning,teacher pedagogical orientation and practices and student use of inquiry, discussion, using technology as a learning tool). An inter-computers, most of these studies relied on self-report data from rater reliability study of SOM with trained observers was conductedteachers. As several researchers point out, teachers usually have by Lewis et al. (1999). The study indicated that pairs of observerssome notion concerning desirable answers, so these types of data selected the identical response on the five-category rubric on 67%may be unreliable and biased or provide limited and invalid of the observation form items. Agreement within one categoryinformation (Hakkarainen et al., 2001; Kopcha & Sullivan, 2007). occurs 93.8 of the time and within two categories 100% of the time.Furthermore, Hakkarainen et al. (2001) indicated that there is even A more recent reliability study (Sterbinsky & Burke, 2004) founda discrepancy between teachers’ pedagogical perspectives and their similar results in that observer ratings were within one category forreported classroom practices. Ertmer, Gopalakrishnan, and Ross 96% of the whole-school observations and for 91% of the targeted(2001) suggest that researchers should focus on what teachers are observations.doing in terms of beliefs and practices regarding computer use inthe classrooms. Therefore, it is important to observe and record 2.2.2. SCUtype of computer software and how and to what extent these The SCU is a companion instrument to the SOM and was alsoapplications are used in actual classroom settings. This study used during the targeted observations (Lowther & Ross, 1999). Theexamined the pattern between types of computer applications and SCU was designed exclusively to capture student access to, abilityclassroom practices based on realistic data gathered by direct with, and use of computers, rather than teacher use of technology.
    • 542 F.A. Inan et al. / Teaching and Teacher Education 26 (2010) 540–546 Observers record computer activities by the software being experiential/hands-on learning, systematic individual instruction,used. The computer activities are divided into three categories sustained writing/composition, sustained reading, independentbased on the type of software used: (a) production software (word inquiry/research on the part of students, student discussion). Eachprocessing, databases, spreadsheets, draw-paint graphics, presen- of the variables was coded as not observed (rubric category ¼ 0)tation, authoring, concept mapping, and planning), (b) Internet or and observed (categories 1–4 combined). Results did not includeresearch software (Internet browser, CD reference materials, and analyses that had an expected count of less than five (Huck, 2008;communications), and (c) educational software (drill-practice- Sheskin, 2000).tutorial, problem solving, and process software). Early interraterreliability of SCU was determined in a study that involved pairs of 3. Resultstrained observers who conducted observations in 42 targeted visitsto classrooms that were scheduled to have students utilizing 3.1. Student computer activitiestechnology. Results from the study revealed that overall, the pairedobservers selected the identical SCU response on 86% of the items, SCU results indicate that the students were using a variety ofwith all other responses being only one rating apart (Lowther & software applications during classroom observations. InternetRoss, 1999). A more recent reliability study for the SCU (Sterbinsky browser was the most commonly observed application as it was& Burke, 2004) show that observer ratings were within one cate- observed being used by students rarely to extensively in nearly 60%gory for 91% of the targeted observations. of the classrooms. In nearly 25% of the classes, other software observed in the range of rarely to extensively were word processing2.3. Procedures (22.1%), drill/practice/tutorials (21.4%), and presentation (21.3%). Database, concept mapping, communications, and process software In this study, the SOM and SCU was used during targeted were the least observed software, which were being utilized in lessobservations to explore classroom practices in prearranged 1-hour than 5% of the visits. Authoring software was the only software notsessions in which the teachers were asked to integrate technology. observed. Table 1 depicts the observed student computer activities.Observed strategies and student computer activities were recordedon SOM and SCU Notes forms that represented 15 minutes of 3.2. Instructional strategiesobserved time. At the conclusion of the visit, the observersummarized, on data summary forms, the frequency with which SOM data revealed that the most commonly observed strategieseach of the strategies and the computer activities /and software across all classes were teacher acting as a coach or facilitatorwere observed. The frequency for both instruments was recorded (90.1%), direct instruction (72.7%), use of higher-level questioningusing a five-point rubric that ranges from (0) Not Observed to (4) (46.8%), cooperative or collaborative learning (46.2), and project-Extensively observed. To ensure the reliability of data, observers based learning (42.7%). Systematic individual instruction andparticipated in a comprehensive training session. An observer’s parent/community involvement in learning activities were onlymanual provided definition of terms, examples and explanations of observed in less than 5% of the observations. In the majority of thethe target strategies, and a description of procedures for observations (85.3%), technology was used as a learning tool orcompleting the instrument. After the training session, each resource more commonly than for instructional delivery (55.2%).observer also participated in sufficient practice exercises in real Table 2 presents the observed classroom activities.classroom settings to ensure that his/her data were comparablewith those of experienced observers. Observation data from TLCF and EdTech schools were collected 3.3. Type of software and instructional strategiesby trained observers and both SOM and SCU were used during theobservations. Four targeted observations for each of the 26 TLCF The chi-square analysis revealed that word processing, presen-schools and three-targeted observation for each of the 13 EdTech tation and Internet had a significant relationship with student-schools were conducted. Teachers from each grant school were centered activities. This included collaborative learning, integrationrandomly selected and informed prior to the observation to of subject areas, project-based learning, independent inquiry, anddemonstrate a prepared lesson using technology. Observersworked with the teachers, technology coaches, and administrators Table 1to schedule all data collection events. Frequency of student computer activities (N ¼ 143). NO (%) R (%) O (%) F (%) E (%)2.4. Data analysis Production software used by students Word processing 77.9 5.0 2.9 5.0 9.3 Observation data were analyzed by descriptive statistical tech- Database 97.1 0.7 2.2 0.0 0.0niques including frequencies, percentages, means and standard Spreadsheet 90.7 1.4 0.0 2.9 5.0deviations. Furthermore, two-way contingency table analyses Draw/paint/graphics/photo-imaging 88.6 0.0 3.6 2.1 5.7(chi-square for independence) were conducted to determine if Presentation 78.7 2.8 4.3 5.7 8.5 Authoring 100 0.0 0.0 0.0 0.0relationships existed between the four most commonly used soft- Concept mapping 95.7 0.7 0.0 0.0 3.6ware applications and the 17 most frequently observed instruc- Planning 99.3 0.0 0.7 0.0 0.0tional strategies. The most commonly used software applications Internet/research software used by studentswere Internet browser, word processing, drill and practice, and Internet browser 40.1 3.5 2.8 12.0 41.5presentation. The instructional strategies consisted of four orien- CD reference 93.6 2.1 2.1 0.7 1.4tations (direct instruction, team teaching, cooperative learning, and Communications 97.8 1.4 0.0 0.0 0.7individual tutoring), six instructional strategies (higher-level Educational software used by studentsinstructional feedback, integration of subject areas, project-based Drill/practice/tutorial 78.6 2.9 6.4 4.3 7.9learning, use of higher-level questioning strategies, teacher acting Problem-solving 94.9 1.4 0.0 2.2 1.4as a coach/facilitator, parent/community involvement in learning Process software 97.1 0.7 0.7 0.0 1.4activities), and seven student activities (independent seatwork, 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 543Table 2 (e.g., production and research) rather than used for instructionalFrequencies of instructional strategies used (N ¼ 143). delivery in the majority of observations. In other words, teachers NO (%) R (%) O (%) F (%) E (%) implemented student-centered strategies more frequently thanInstructional orientation teacher-centered strategies. For example, teachers acted as a coach Direct instruction (lecture) 27.3 24.5 13.3 18.2 16.8 or facilitator rather than lecturer when technology was integrated Team teaching 84.6 1.4 2.8 4.2 7.0 as a learning tool in the lesson. Moreover, use of higher-level Cooperative/collaborative learning 53.8 4.2 9.8 17.5 14.7 questioning, cooperative and project-based learning were observed Individual tutoring 88.8 5.6 4.2 1.4 0.0 in almost one-half of the observations. These results contrastInstructional strategies previous studies which showed the computers primarily being Higher-level instructional feedback 60.8 12.6 12.6 7.7 6.3 Integration of subject areas 72.7 2.1 7.0 9.1 9.1 used for instruction delivery (e.g., tutorial or drill and practice) Project-based learning 57.3 2.8 4.2 13.3 22.4 rather than a tool to facilitate student learning and engagement Use of higher-level questioning strategies 53.2 15.6 16.3 9.2 5.7 (Lowther et al., 2003; Niederhauser & Lindstrom, 2006; Ross & Teacher acting as a coach/facilitator 9.9 5.0 14.2 31.2 39.7 Lowther, 2003; Smeets & Mooij, 2001). Parent/community involvement 96.5 0.7 0.7 0.7 1.4Student activities 4.2. Relations between instructional strategies and type Independent seatwork 48.3 9.1 7.7 14.7 20.3 of computer software Experiential, hands-on learning 65.0 2.8 6.3 14.0 11.9 Systematic individual instruction 95.8 0.7 1.4 2.1 0.0 Sustained writing/composition 83.9 3.5 6.3 3.5 2.8 As previously mentioned, word processing is one of the most Sustained reading 87.4 5.6 3.5 2.1 1.4 commonly used software applications in K-12 because it is easy to Independent inquiry/research 57.0 5.6 9.2 12.0 16.2 use and enables students to create and edit more visually appealing Student discussion 69.2 9.8 4.9 9.8 6.3 and grammatically accurate products (Morrison & Lowther, 2010;NO ¼ Not Observed, R ¼ Rarely, O ¼ Occasionally, F ¼ Frequently, E ¼ Extensively. Norton & Sprague, 2001). According to the findings, word processing was found to be positively related to several student- centered activities including cooperative learning, integration ofstudent discussion. Drill and practice applications showed subject areas, project-based learning, sustained writing, indepen-a dissimilar pattern compared to other computer applications. dent inquiry and student discussion. Some of the relationships suchThese applications were most commonly used for independent as project-based learning, integration of subject areas, andseatwork and instructional delivery. Table 3 summarizes the asso- sustained writing can be logically explained. However, the rela-ciations between software applications and instructional strategies. tionship between word processing and collaborative learning and student discussion was less obvious. Although word processing is4. Discussion typically considered a way to enhance individual productivity, it can allow students to work on writing activities in a group (Forcier,4.1. Student computer use and classroom activities 1996). These activities can be a result of incorporating collaborative learning or from the lack of computers in classroom (Kumpulainen In terms of the usage of computer applications in the class- & Wray, 1999; Mumtaz & Hammond, 2002). In this study, studentsrooms, the results showed that although various software appli- were observed working at computers in pairs during at least 20% ofcations were being used by the students, the Internet browser was the observations. It is more likely that groups of students usingthe most commonly observed application. Other software observed word processing may work collaboratively to brainstorm ideas orrarely to extensively, in nearly 25% of the classes, were word pro- conduct research for a writing project.cessing, drill and practice, and presentation. Understandably, The findings revealed that draw/paint/graphics/photo-imagingstudies conducted when the Internet was first introduced to applications were positively related with independent seatwork.schools showed that drill and practice and word processing, rather This is understandable because a student working with or creatingthan the Internet, were the most commonly used software graphics is more likely to work alone. In a writing activity, two or(McGraw, Blair, & Ross, 1999; Reichstetter, 2000; Ross & Lowther, more students may discuss a topic and then compose a joint2003). However, more recent studies reflect results similar to this representation of their understanding. On the other hand, thestudy in that they revealed an increased use of Internet (Bennett & nature of the drawing or editing a photo may not lend itself asPye, 2003; Grant et al., 2005; Lowther, Strahl, Inan, & Bates, 2007). easily to the input of multiple students.Researchers suggest that this shift is probably a part of movement Presentation software was found to be related with threeaway from traditional drill and practice use of the computer to student-centered activities: integration of subject areas, project-more project-oriented student-centered and collaborative activi- based learning, and student discussion. This relationship can beties (Lindstrom & Niederhauser, 2003; Liu, 2004; Niederhauser & explained by affordance of the software. First, presentations helpLindstrom, 2006). students to present their ideas or artifacts of project-based learning In this study, extent of computer application usage was broad; to other students (Norton & Wiburg, 2003). These presentationsranging from moderate (60%) to not observed at all. The results can lead to discussions between students. Second, presentationcould possibly be attributed to two main factors: the innate func- software (e.g., PowerPoint) can be used as an authoring softwaretions and attributions of the software and teacher proficiency with allowing students to create interactive multimedia products thatthe software. For example, word processing is fundamental to address more than one subject area (Garcia, 2004).writing reports, essays, and other forms of writing activities that are One of the critical elements of today’s classrooms is access to thethe main component of student work for all grade levels and subject Internet. Through means of the Internet, students are providedareas. In a related study by Muir-Herzig (2004), the author found opportunities to search, discover, and utilize information thatthat students most commonly used word processing and Internet meets individual learning goals (Chen & Paul, 2003; Jonassen, Peck,during classroom activities. They also found that teacher profi- & Wilson, 1999; Morrison & Lowther, 2010). The current findingsciency on these two computer applications was similarly very high. revealed that there were positive relationships between the In regard to classroom practices, the results of this study Internet and student-centered activities. These activities involvedrevealed that computers were used as a learning tool conducting research, collaboration among students, and the
    • 544 F.A. Inan et al. / Teaching and Teacher Education 26 (2010) 540–546Table 3Summary of strategies showing significant association with computer applications. Word Processing Drawing Presentation Internet DrillInstructional orientation Direct instruction (lecture) Team teaching Cooperative/collaborative learning C C Individual tutoringInstructional strategies Higher-level instructional feedback Integration of subject areas CC CC Project-based learning C CC Q Use of higher-level questioning strategies Teacher acting as a coach/facilitator C Parent/community involvement in learningStudent activities Independent seatwork C Q CC Experiential, hands-on learning Systematic individual instruction Sustained writing/composition CC Sustained reading Independent inquiry/research C CC Student discussion CC CCC ¼ Positive and Significant, p < 0.05,; CC ¼ Positive and Significant, p < 0.01; Q ¼ Negative and Significant, p < 0.05.teacher serving as a facilitator. Consequently, independent seat- technology training and computer experiences can extend anwork was less observed when students used the Internet. understanding of teacher use of technology (Atkins & Vasu, 2000; As would be expected, drill and practice or tutorial applications Robinson, 2003). Similarly, studies should examine how contextualwere used for instructional delivery of subject matter content and barriers influenced instructional practices and teaching strategiespractice exercises. While research has shown positive results of (Dexter, Anderson, & Becker, 1999; Zhao & Frank, 2003). Further-using educational software in specific conditions (Reed, 1996; Reed more, use of software and instructional strategies may differ with& Spuck, 1996), other findings revealed that these applications can respect to grade level or subject area of the classroom (Newhouse &have some drawbacks and limitations (Forcier, 1996; Solmon & Rennie, 2001; Ruthven, Hennessy, & Brindley, 2004). Therefore,Wiederhorn, 2000). The findings of this study showed that drill and further research may account for grade level and subject areas.practice applications had a negative relationship with project- Future studies may also employ mixed method research tobased learning, while exhibiting a positive relationship with inde- incorporate quantitative research methods along with qualitativependent seatwork. Drill and practice activities are completed data (e.g., observation, interviews), as well as data collected fromindividually; therefore, they may not allow active student principals’, parents’, and students’ perceptions and experiencesengagement in the learning process. Moreover, drill and practice (Creswell, 2009; Creswell & Plano Clark, 2007; Tashakkori &activities limit collaboration between students (Morrison & Low- Teddlie, 2003). Such rich data would provide useful insights intother, 2010). understanding technology integration in K-12 schools (Baylor & Ritchie, 2002; Judson, 2006; Ruthven et al., 2004). The findings of5. Conclusion this study come from structured observation data (Painter, 2001). There are many advantages of using classroom observation. This study showed that classroom practices tend to be more Well-designed observations can provide sufficient data andstudent-centered when technology is integrated into lessons where evidence on the effective use of technology in the classroomstudents use production or research software (e.g., word process- (Hilberg, Waxman, & Tharp, 2004). However, a classroom obser-ing, presentation, Internet). In contrast, drill and practice applica- vation technique presents challenges and limitations with regard totions showed a negative relationship to student-centered activities. gathering valid and reliable data. There are concerns regarding theBy providing data from actual classroom practices, the results of amount of time for observation and appropriate number of obser-this study extended the findings of previous studies (c.f, Becker, vation needed, observer effect, or reliability of administered2000; Niederhauser & Stoddart, 2001) that demonstrate relations observation instruments (Dirr, 2006; Volpe, DiPerna, & Hintze,between teachers’ software selection and their pedagogical 2005). The previously mentioned criticisms and limitations do notperspectives. necessarily detract from the value and utility of the observational Although, this study revealed relationships between the soft- method (Painter, 2001; Waxman, Hilberg, & Tharp, 2004). Obser-ware and instructional strategies, it did not examine the direction vations can allow researchers to explore the process of teaching inof this relationship. Further studies can investigate whether the a naturalistic setting, provide information that precisely describescomputer applications lead to use of student-centered strategies or the status of classroom practices, and identify instructional prob-vise versa. This study also did not intend to evaluate the effec- lems (Fish, 2000; Hilberg et al., 2004). If the limitations aretiveness of computer use but, rather the frequency of each software addressed and data collection instruments and processes areuse. Therefore, future studies should consider the quality of carefully designed and administered, classroom observation tech-computer use rather than the amount of use. This study could be niques have promise as reliable and valid classroom measures ofextended by examining the influence of teacher characteristics classroom practice (Dirr, 2006; Patton, 2002)(e.g., age, experience) and school characteristics (e.g., technology Teachers’ pedagogical perspectives and practices appeared toavailability, support) on instructional strategies and software shape the type, amount, and way that technology is utilized in thepreferences (Hew & Brush, 2007). An addition of teachers’ previous classrooms (Ertmer et al., 1999; Niederhauser & Lindstrom, 2006;
    • F.A. Inan et al. / Teaching and Teacher Education 26 (2010) 540–546 545Pajares, 1992; Watson, 2001). Therefore, professional development Dexter, S. L., Anderson, R. E., & Becker, H. J. (1999). Teachers’ views of computers as catalysts for change in their teaching practice. Journal of Research on Computingopportunities for both preservice and in-service teachers should in Education, 31(3), 221–239.mainly concentrate on teachers’ pedagogical readiness and beliefs Dickard, N. (2002). Great expectations: Leveraging America’s investment in educa-to integrate technology (Ertmer, 2005; Gonzales, Pickett, Hupert, & tional technology. Washington, DC: Benton Foundation.Martin, 2002; Lowther, Bassoppo-Moyo, & Morrison, 1998; Parr, Dickard, N. (2003). The sustainability challenge: Taking EdTech to the next level. Washington, DC: Benton Foundation.1999; Yildirim, 2000). However, it is suggested that initially Dirr, P. J. (2006). 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