Peter L.V. Ayala
University of Hawai‘i at Mānoa
The category of mobile computing devices is expanding with the emergence of the very popular “Tablet” device. Tablets potentially may significantly displace the thousands of laptops/netbooks, smartphones, media players and other mobile computing devices being considered by many school districts. Major technology changes are taking place. The introduction of 4G networks enables video streaming and makes content delivery faster. Education is only one of the many industries that will benefit from 4G communications and the Tablet devices designed to operate on them.
This researcher wants to investigate the informal educational technology purchasing social network and gage the potential development and purchasing collaboration between large school districts and the effective uses of public influence over the consumer electronics industry. Specifically, this researcher seeks to assess the desire of decision makers to use public funds to influence the development of mobile devices for education. Considerable public funds are expended on educational technology may be appropriately leveraged to influence and monitor product development and implementation. The potential product improvements and cost savings justify an investigation of the issues.
Statement of the Research Problem
There is a concern that to much public educational technology funding is wasted or misspent. How much are school districts spending on mobile devices, how effective are those devices and who makes the final decision? This project starts the inquiry by collecting baseline information on the technology decision makers within education. In order to formulate strong convincing arguments for future educational technology requirements and budgets, current capabilities and expenditures will be assessed.
The purpose of this mixed method research is to explore the potential of a purchasing collaboration and gage the willingness of school district technology managers/coordinators to participate in the collective development and purchasing of mobile computing devices for education.
Many interesting questions arise when considering the implementation of new technology devices. This researcher seeks to focus on the selection processes of the mobile devices known as Tablets, those choosing them for education and why. The research questions investigated are:
- What is the social network structure of educational technology decision makers?
- Are educational technology decision makers receptive to collaborative purchasing?
- How much influence should educational technology managers have over design specifications?
- How are tablet devices impacting educational technology purchasing decisions?
- Are there opportunities for educational technology managers to collaborate on Internet safety issues?
Tablet computing devices are emerging as many manufacturers rush to compete with Apple Computer’s $500 iPad. Dell Computer Company recently introduced a $300 Tablet device. The expense of these devices has competition from low cost challengers. Nicholas Negroponte, founder and chairman of the One Laptop Per Child (OLPC) initiative to provide developing countries a $100 laptop based on extraordinary innovation in hardware and software that fosters self-learning has had some successes and challenges. (Kraemer, Dedrick, & Sharma, 2009) The XO laptop developed by OLPC, has company in the low cost educational market with India’s Minister of Human Resource Development, Kapil Sibal’s announcement of a $35 Tablet for Indian students. (Negroponte, 2010)
According to The National Center for Education Statistics (NCES), the primary federal entity for collecting and analyzing data related to education, there were 11,200,573 students enrolled in the 100 largest public elementary and secondary school districts in the United States and jurisdictions, by school district: School years 2006–07 and 2007–08. (National Center for Education Statistics, 2010) If these school systems were to purchase tablet devices for the 11,200,573 students it would cost $5,600,286,500 (5.6 billion) for the $500 iPad on the high end and $392,020,055 (392 million) for a $35 device on the low end. This estimate does not include the price of devices for teachers and administrators and subsequent IT-management costs. Nor does it include the cost of teacher training, additional software, and ongoing maintenance and support. (Kraemer, et al., 2009)
Matt Villano in his article, Procurement >> Buying Power, outlines existing collaboration efforts and challenges in higher education. (Villano, 2006) This research is important because it seeks to investigate the potential for similar collaborations among the 100 largest public elementary and secondary school districts in the United States. The significant cost savings and other benefits are possible if there is a willingness of the informal social network to develop collaboration.
The Social Network Analysis (SNA) research tradition has some limitations that merit discussion. In their article, Rixon, Callahan and Schenk (2006) suggest that “Social Network Analysis needs to move beyond mere analysis and overcome 3 big problems: engendering trust, dispelling the illusion of accuracy, and taming the expert mindset” (Rixon, Callahan, & Schenk, 2006). The issue of trust creates a limitation because “unlike many forms of survey which use anonymity as a protective mechanism for participants, the very power of social network analysis depends on people explicitly disclosing their relationships with others. (Rixon, et al., 2006) The illusion of accuracy is a limiting factor because of the measurement approach used in SNA. “Commonly used are centrality measures such as indegree, betweenness and close-ness. The robust use of these measures assumes the underlying data sets are accurate. Such accuracy is in fact rare and missing data is more commonplace” (Rixon, et al., 2006). The last limitation discussed by Rixon et al. is the expert mindset that creates an expectation and a dependency on the researcher and dis-empowers the entity promoting the research. Finally, “for social network analysis to move to the next level, moving beyond merely analysis, there is a need to move the role of researcher/consultant from ‘expert’ towards ‘facilitator”. (Rixon, et al., 2006)
A full text, references available, scholarly, peer reviewed, journal search of the Educational Resource Information Center (ERIC) education database, via Ebesco Host was preformed. Additionally, Academic Search Premier, Health Source: Nursing/Academic Edition and Health Source – Consumer Edition, Consumer Health Complete – EBSCOhost, Small Business Reference Center and Public Administration Abstracts databases were selected as part of the search. The query was limited to years 2003 to 2010; using the key words “Collaborative Purchasing” this search query yielded 3 results. Due to the limited results, a second ERIC query adding the key words “VBP (Value Based Purchasing)” was initiated and yielded 1 reference.
Two key studies were selected from the review of literature, “Are Employers Pursuing Value-Based Purchasing?” (Maio, Hartmann, Goldfarb, Roumm, & Nash, 2005) and “Let’s stick together: collaborative purchasing of electronic journals in the National Health Service” (Marriott, 2008). These key studies are good examples of cost saving collaboration research. The research methods used provide an excellent framework and will be replicated in this study.
Research Design and Methodology
Quantitative and qualitative data will be collected and evaluated utilizing Social Network Analysis (SNA). This research study is designed to help clarify the interest in collaborative Tablet device purchasing and the willingness of large K-12 school districts to impact the development of mobile computing devices for education. The study also seeks to measure the Internet safety initiatives in use and to gain insight into barriers preventing their standardization and wider implementation.
Description of Research Methodology
Social Network Analysis “SNA is based on an assumption of the importance of relationships among interacting units. The social network perspective encompasses theories, models, and applications that are expressed in terms of relational concepts or processes” (Wasserman & Faust, 1994). Informal educational technology social networks already exist as a result of organizational requirements and the existence of professional societies. SNA is an appropriate method for defining the decision makers relevant to this study, answering the research questions and to address the potential of organizing to reduce the growing expense of educational technology. The research conducted by Maio et al. in the article titled: “Are Employers Pursuing Value-Based Purchasing?” provides an excellent framework for replication. The following methods are paraphrased from this key study.
The population for this study is comprised of the representatives from the 100 largest school districts in the United States of America as determined by The National Center for Education Statistics (NCES), the primary federal entity for collecting and analyzing data related to education. The educational technology purchasing managers or the individuals responsible for technology in these school districts are the target respondents of this research study. The participants where selected because of their key positions within the educational technology evaluation and purchase decision making process. The opinions of these participants are valuable when discussing educational technology products, implementation, effectiveness and safety. Participation is optional and ethics questions are covered by participant’s IRB permission and consent release.
School districts will be contacted to identify the most knowledgeable individual within the organization with regard to tablet evaluation and purchasing. It is assumed that the individuals represent the views of their school districts. The survey instrument consists of questions pertaining to a variety of topics. The questions are designed to:
• Capture SNA demographic information about educational technology managers and school districts
• Reveal factors entering into K-12 tablet purchasing decisions
• Describe the district’s commitment to collaborative purchasing
• Determine factors motivating schools to pursue collaborative purchasing activities and barriers affecting schools when, or preventing schools from, engaging in collaborative purchasing activities.
Data Collection and Recording
To ensure validity/trustworthiness a convenience sample of schools will test the instrument. After being pilot tested the instrument will be formatted for online administration on www.surveymonkey.com a Web-based survey portal. Prior to the implementation of the survey, the investigators will access the instrument through a variety of common Web portals in order to verify the accessibility and reliability of the survey site. A letter explaining the purpose of, and providing instructions regarding how to access, the Web-based survey will be sent by mail and/or e-mail to all potential participants. In this letter, the name and phone number of a contact person will be provided, so the participants can request a printed copy of the instrument or decline participation.
A gift certificate will also be included as an incentive for participation. Two follow-up letters will be sent in two-week intervals to all sample members who had not identified themselves as respondents or as unwilling to participate. The survey will be closed after 11⁄2 months. Participation will be voluntary and confidential.
More here, analytical procedures to answer questions/hypotheses. All responses will be entered into the form on the survey web site, either by the respondents themselves or, for respondents who complete the printed instrument, by a study staff member. The complete data file will be subsequently downloaded in the form of a spreadsheet. Descriptive statistics will be calculated for all variables using SPSS data analysis software.
The safety concerns and factors entering into K-12 tablet purchasing decisions are as new as the devices entering the market. Capturing the demographic information of educational technology managers and their school districts is important in understanding the current informal social network. Through this understanding it is possible to analyze their interest, motivation and desire to formalize a commitment to collaborative purchasing. This investigator’s expectation is that there may be barriers preventing schools from engaging in collaborative purchasing activities. However the potential for saving taxpayer dollars and providing secure devices justifies an investigation into the social network and it’s potential collaborative purchasing activities.
The results of this research may be significant not only to the field of education but also significant in affecting the consumer electronics industry in a similar way that the OLPC has been credited with spurring the netbook market. (Kraemer, et al., 2009) Through collaboration educational technology managers might enjoy the challenge and benefits of greater influence over product development. The potential cost savings could spread to other areas of society. A reduction of consumer electronics cost might help improve the global economic climate by restoring consumer wealth. Finally, the opportunities for educational technology managers to collaborate on Internet safety issues may help to protect students in an unprecedented way.
Kraemer, K. L., Dedrick, J., & Sharma, P. (2009). One Laptop Per Child: Vision vs. Reality. [Article]. Communications of the ACM, 52(6), 66-73.
Maio, V., Hartmann, C. W., Goldfarb, N. I., Roumm, A. R., & Nash, D. B. (2005). Are Employers Pursuing Value-Based Purchasing? [Article]. Benefits Quarterly, 21(3), 20-29.
Marriott, R. (2008). Let’s stick together: collaborative purchasing of electronic journals in the National Health Service. [Article]. Health Information & Libraries Journal, 25(3), 218-224. doi: 10.1111/j.1471-1842.2007.00763.x
National Center for Education Statistics. (2010). Characteristics of the 100 Largest Public Elementary and Secondary School Districts in the United States: 2007–08. Table A1. Selected statistics for the 100 largest public elementary and secondary school districts in the United States and jurisdictions, by school district: School years 2006–07 and 2007–08, 2010, from http://nces.ed.gov/pubs2010/100largest/tables/table_a01.asp?referrer=report
Negroponte, N. (2010). Welcome: $35 tablet for education. Retrieved from http://blog.laptop.org/2010/07/29/welcoming-indias-tablet/
Rixon, A., Callahan, S., & Schenk, M. (2006, Posted on April 7, 2006 11:02 AM). 3 Big Problems for Social Network Analysis, from http://www.anecdote.com.au/archives/2006/04/3-big-problems.html
Villano, M. (2006, 02/03/06). Procurement >> Buying Power, 2010, from http://campustechnology.com/Articles/2006/02/Procurement–Buying-Power.aspx?Page=1
Wasserman, S., & Faust, K. (1994). Social Network Analysis: Methods and Applications: : Cambridge University Press.