Decisions, Decisions: Planning and Implementing Technology-Integrated Lessons in Special Education Classrooms
Participate and share : Poster
Sunday, June 23, 11:30 am–1:30 pm
Location: Posters: Level 4, Terrace Ballroom Lobby, Table 20
Dr. Sue Anderson Dr. Rebecca Putman
Results of this qualitative study illustrate special education teachers' decision-making process while planning and implementing technology-based instruction. The findings contribute to a developing strand of research that focuses on how special education teachers exhibit TPACK in their reasoning and practice and provide a basis for professional development efforts.
|Audience:||Teachers, Teacher education/higher ed faculty, Technology coordinators/facilitators|
|Attendee devices:||Devices not needed|
|Focus:||Digital age teaching & learning|
|Topic:||Special populations/assistive and adaptive technologies|
|Subject area:||Special education|
|ISTE Standards:||For Coaches:
Teaching, Learning and Assessments
Equity and Citizenship Advocate
Teachers use their knowledge of technology, pedagogy, and content strategically when making decisions about integrating technology into instruction (Koehler, Mishra, & Cain, 2013). Technological and pedagogical content knowledge (TPACK) can be defined as teachers’ knowledge of when, where and how to use technology while guiding students to increase their knowledge and skills in particular content areas using appropriate pedagogical approaches (Brantley-Dias & Ertmer, 2013; Niess, 2011). The TPACK model emphasizes the complex interactions among teachers’ knowledge of technology, pedagogy, and content, which vary depending on context and other factors, such as confidence, experience, and beliefs (Anderson & Putman, 2018; Brantley-Dias & Ertmer, 2013; Koehler et al., 2013; Niess, 2011).
A developing strand of TPACK research focuses on how teachers exhibit TPACK in their reasoning and practice (Harris, Phillips, Koehler, & Rosenberg, 2017). For example, researchers found that the most frequent reasons general education teachers used technology included supporting educational goals, facilitating the learning process, conducting formative assessment, and individualizing instruction based upon students’ needs (Heitink et al., 2016). The teachers’ educational beliefs tended to match their practice; they were more inclined to use technology for knowledge-transfer than knowledge construction activities. Teachers who combined technological, pedagogical, and content knowledge used technology in ways that were essential to accomplishing educational goals or pedagogical practices.
General and special education teachers possess different professional knowledge structures, which they use to interpret classroom events, identify, and solve instructional problems (Blanton et al., 1994). Research on special educators’ decision-making (without technology) indicates that they possess extensive and detailed knowledge about students that helps them to monitor and effectively address needs by being very responsive to students’ academic, behavioral, and emotional states (Stough & Palmer, 2003). Their instructional decision-making relies upon close observation of students’ behavior and attention, as well as knowledge of student characteristics and educational practices related to curriculum, content, and pedagogy. Special education teachers use a variety of strategies to assist students when they have difficulty completing tasks.
Out of more than 1,000 publications about TPACK (Harris et al., 2017), we located only a few qualitative studies that pertained to inservice special education teachers. In a previous study of eight elementary special education teachers, we found interrelationships among TPACK, teaching experience, confidence with using technology, beliefs about the role of technology in education, and perceptions of the benefits and challenges associated with using it (Anderson & Putman, 2018). In another study of 10 exemplary technology-using special education teachers, researchers found that technology-related decisions often occurred serendipitously, as teachers identified student needs in the moment, and then selected and integrated technology using a trial-and-error process (Courduff, Szapkiw, & Wendt, 2016). A third study of three inservice special educators demonstrated that teachers increased their TPACK, self-efficacy, willingness, and ability to plan and implement technology-based literacy lessons through well-designed professional development activities (Ciampa, 2017).
Six female special education teachers at two schools participated in the study. Half taught at one school and half at the other. They met the criteria for inclusion in the study since they had access to technology that could be used to support instruction, taught students who have been identified as having mild disabilities, and used technology during instruction. We selected the six participants out of a pool of 12 teachers who participated in a larger study conducted during 2016-2017, based upon their confidence with using technology, grade level, and subject area. The teachers were all fairly confident about using technology in the classroom. They taught students from Kindergarten through seventh grade in the following content areas: language arts, math, science, social studies, and art. Their teaching experience ranged from 8-20 years, with an average of 13.5. Four of the six teachers held master’s degrees. Three of the teachers held degrees in special education; one was an art educator, one a reading specialist, and two were alternatively certified.
All participants taught at private schools for students with mild disabilities in the southwestern United States. One school was a K-6th grade laboratory school for children with mild disabilities at a private university. The other was a private K-12th grade school for children who learn differently. Both schools had small class sizes, provided specialized instruction, and created supportive learning environments to improve the academic and personal success of students who had struggled in traditional schools. Students’ exhibited characteristics of disabilities such as attention deficit hyperactivity disorder, learning disabilities, and/or high functioning autism. The students faced various challenges, including expressive and receptive language deficits, cognitive or auditory processing difficulties, and issues with reading, writing and/or math. Other challenges involved attention, memory, executive functioning, communication, behavior, and social/emotional well-being.
At one school, most classrooms had a smartboard, projector or large TV monitor, a computer for the teacher, and several desktop computers for student use. Most students had their own iPad, which was kept at school. At the other school, each teacher had a computer or tablet and projector, and one teacher had a smartboard. Only the 7th graders had their own PC tablets; the rest of the students had shared access to tablet computers with touch screens that were kept on a cart. Both schools provided several comprehensive programs, such as Lexia, Mathletics, and Accelerated Reader. Teachers also reported using many kinds of digital tools, such as BrainPOP, Quizlet, Kahoot, Flowcabulary, IXL, MyHomework, and Go Noodle, as well as productivity software or apps, such as Microsoft Word, PowerPoint, Photoshop, iMovie, Google Docs, Book Creator, and Notability.
We interviewed each participant three times, once at the beginning of the school year, and once after each of two observations of technology-integrated lessons. We collected data from three of the participants during the 2016-2017 school year and the other three in the fall of 2017. We used a small digital video camera with a wide-angle lens to record the observations and a digital audio recorder to capture the interviews. A professional service transcribed the audio recordings. We also made detailed field notes during the observations and kept research journals summarizing each observation and interview to identify potential themes that could be used when developing a coding system for data analysis. Each researcher did about half of the interviews and observations, watching every teacher at least once.
The post-observation interviews, which occurred within 24 hours of the observations, probed the teachers’ thinking process while planning and implementing lessons. We used stimulated recall to identify the instructional decisions made during the lesson and the teachers' reasons for making those decisions. Stimulated recall allows researchers to investigate cognitive processes, often using video or audio recordings to help participants recall and describe their thought process during an experience (Vesterinen, Toom, & Patrikainen, 2010). To identify decisions made during a lesson, the researcher first asked the teacher to describe any decisions that she remembered. To stimulate recall of additional decisions, the researcher referred to her notes and asked about specific instances in which it looked like the teacher made a decision (e.g., changed what she was doing). To stimulate additional recall, if necessary, and when time permitted, the researcher played back parts of the video recording and asked the teacher to discuss what she was thinking during that time.
We utilized thematic qualitative data analysis techniques to identify patterns and themes in the interview transcripts. We checked the transcripts for accuracy, corrected any errors, and then uploaded the transcripts to Dedoose (http://www.dedoose.com/), which we used to code and analyze the data. We also reviewed notes from classroom observations and interviews, research journals, and audio and video recordings, if necessary, for purposes of clarification.
During the first round of coding, we used inductive thematic analysis in which we divided the text into segments, labeled them, and identified emerging themes and patterns in the data. We started off by independently coding two transcripts. We then identified differences in the excerpts selected and codes applied, resolved the discrepancies through discussions, and made changes to the coding scheme until achieving consistency. Next, we divided up the rest of the transcripts for independent coding. For each transcript, we reviewed each other’s coded excerpts, noted disagreements, and discussed them until reaching consensus.
In the second phase of the analysis, we used a deductive thematic approach to identify the TPACK domains reflected in the excerpts selected during the first round of coding. One of us coded the TPACK dimensions, the other noted disagreements, and then we resolved those disagreements. Initial data coding is nearly complete, and data analysis should be finished by December 2018. Below we describe some preliminary results based upon review of the coded excerpts that reflected planning or in-the-moment instructional decisions.
Our preliminary examination of the data suggests that the technology-integration process is complex, requiring thoughtful and purposeful decision-making. When making instructional decisions, teachers drew upon components of TPACK, including their in-depth knowledge of what best helped students to be engaged and successful considering their learning strengths and challenges. During and after instruction, teachers monitored and reflected upon students’ behavior and responses during instruction so that they could adjust instruction accordingly. Teachers’ decisions about using technology were related to their beliefs about the role of technology in the classroom; their perceptions about the benefits and challenges of using it; extensive knowledge of their curriculum; familiarity with their students’ characteristics, needs and preferences; understanding of effective teaching strategies and learning environments; awareness of the affordances and constraints of various digital and non-digital materials; and knowledge of how to use specific technologies. When selecting digital materials, teachers thought about the extent to which the materials aligned with curriculum, provided varied representations of content, produced formative assessment data, facilitated differentiation, enhanced motivation, and fostered the development of academic and life skills.
This study provides insight into teachers’ reasoning and action when planning for and implementing technology in special education classrooms. It contributes to the scarce body of knowledge on the application of the TPACK model in special education contexts. Understanding the decision-making processes of inservice special education teachers regarding technology integration can inform teacher education and professional development efforts to promote special education teachers’ effective use of technology. By better understanding the kinds of decisions teachers make and the knowledge and beliefs underlying those decisions, educational leaders, technology coaches, and teacher educators can better develop and provide effective learning experiences for special educators that enhance their ability to use technology to differentiate instruction, engage students in appropriately-challenging activities, and use formative assessment to gauge student understanding and adapt instruction accordingly to meet their needs.
Anderson, S., & Putman, R. (2018). What were they thinking? Special education teachers’ views on technology integration. Paper presented at ISTE 2018, Chicago, IL. Retrieved from https://conference.iste.org/uploads/ISTE2018/HANDOUTS /KEY_110768282/ SpecialEducationTeachersTechnologyIntegrationAndersonPutman_RP.pdf
Blanton, L. P., Blanton, W. E., & Cross, L. S. (1994). An exploratory study of how general and special education teachers think and make decisions about students with special needs. Teacher Education and Special Education, 17(1), 62-74. doi: 10.1177/088840649401700107
Brantley-Dias, L., & Ertmer, P. A. (2013). Goldilocks and TPACK: Is the construct “just right?” Journal of Research on Technology in Education, 46(2), 103-127. Retrieved from https://www.iste.org/resources/Product?ID=2973
Ciampa, K. (2017). Building bridges between technology and content literacy in special education: Lessons learned from special educators’ use of integrated technology and perceived benefits for students. Literacy Research and Instruction, 56(2), 85-113. doi:10.1080/19388071.2017.1280863
Courduff, J., Szapkiw, S., & Wendt, J. L. (2016). Grounded in what works: Exemplary practice in special education teachers’ technology integration. Journal of Special Education Technology, 31(1), 26-38. doi:10.1177/0162643416633333
Harris, J., Phillips, M., Koehler, M., & Rosenberg, J. (2017). TPCK/TPACK research and development: Past, present, and future directions. Australian Journal of Educational Technology, 33(3), i-vii. Retrieved from https://ajet.org.au/index.php/AJET/issue/ view/124
Heitink, M., Voogt, J., Verplanken, L., van Braak, J., & Fisser, P. (2016). Teachers’ professional reasoning about their pedagogical use of technology. Computers & Education, 101, 70-83. doi:10.1016/j.compedu.2016.05.009
Koehler, M. J., Mishra, P., & Cain, W. (2013). What is technological pedagogical content knowledge? Journal of Education, 193(3), 13-19. Retrieved from http://www.bu.edu/journalofeducation/files/2014/02/BUJoE.193.3.Koehleretal.pdf
Niess, M. L. (2011). Investigating TPACK: Knowledge growth in teaching with technology. Journal of Educational Computing Research, 44(3), 299-317. doi:10.2190/EC.44.3.c
Siuty, M. B., Leko, M. M., Knackstedt, K. M. (2018). Unraveling the role of curriculum in teacher decision making. Teacher Education and Special Education, 41(1), 39-57. doi:10.1177/0888406416683230
Stough, L. M., & Palmer, D. J. (2003). Special thinking in special settings: A qualitative study of expert special educators. The Journal of Special Education, 36(4), 206-222. doi:10.1177/002246690303600402
Vesterinen, O., Toom, A., & Patrikainen, S. (2010). The stimulated recall method and ICTs in research on the reasoning of teachers. International Journal of Research & Method in Education, 33(2), 183-197. doi:10.1080/1743727X.2010.484605