How do computers fit into a plan for pre-Kindergarten children?

Another brief paper that I submitted earlier this semester (Spring '09) at George Washington University:

In this week’s studies in usage of technology in pre-Kindergarten settings, we were introduced to a multi-faceted and often confusing discussion (which might be better characterized as “argument” or “controversy”) over the proper role that modern technologies might play in a pre-Kindergarten classroom. I find it necessary, in order to a bit more dispassionately focus on the question at hand, to take up a curriculum-driven approach to usage of educational technologies in this context. This avoids for the moment the passion-inciting question of whether such technologies are healthy or “proper” for usage with 3 and 4 year-old pre-Kindergarten students, and focuses instead on these two questions: (1) What are the prime goals of the average pre-Kindergarten curriculum? and (2) Could the achievement of these goals be assisted by computer technology?

What are the prime goals of the average pre-Kindergarten curriculum?
For starters, the National Institute for Early Education Research [NIEER] offers this consolation to those of us seeking to make sense of widely disparate pre-Kindergarten curricula throughout the U.S.: “Given the multitude of available curriculum models, the confusion regarding which ones are appropriate for 3- and 4-year-olds is understandable” (Frede & Ackerman, 2007). Determined, however, to find a common thread, I looked at the curricula of a couple of Head Start programs as well as the pre-K curriculum of my neighborhood international school (IST, 2008). All the curricula I examined seemed to converge at a point clearly established by the Head Start program in Portland, Oregon: “The goal … is to bring about a greater degree of social competence in children” (Head Start - Portland, 2009). While some pre-K programs go notably further in their curriculum, stipulating that children will “develop beginning reading skills … acquire beginning writing skills,” etc. (Head Start - New Castle County, 2009), the most fundamental focus of all programs seems to be the development of cooperative social behavior.

One thing that is clearly not present in any pre-Kindergarten curriculum that I have examined is a particular focus on “computer skills”. Whereas many K-12 curricula do pointedly include the development of computer skills, such an explicit role for computers within the pre-Kindergarten curriculum is conspicuously absent. This is important to note: K-12 curricula require the usage of computers; pre-Kindergarten curricula do not. This means that the inclusion of computers in pre-K classrooms seems to be decidedly optional from a curricular perspective.

Could the achievement of these goals be assisted by computer technology?
For the sake of brevity, I will presume that an assessment of technologies which aid in development of reading and writing skills will be covered in our upcoming survey of K-12 educational technologies. This allows a focus on the question of whether the purely socialization-oriented goals common to all pre-K programs can be assisted by incorporation of computer technologies.

In summarizing the findings of neuroscientific research, a recent NIEER report concludes that “sensitive interactions with adults do more to promote brain development than any toy, CD, or DVD” (Thompson, 2008). While this certainly favors humans over gadgets in the pre-K classroom, it leaves open the question as to whether gadgets, such as computers, might play an effective supporting role. Fortunately, I found two relatively recent studies (from 2002 and 2003) which focus on computers and socialization of preschoolers.

One study focused on both the peer-to-peer interactions and student-to-teacher interactions around two separate computers, equipped with a variety of age-appropriate educational games, placed for observation side by side in a preschool classroom. One student was placed at each of the two computers, and the main thrust of the study was to see whether this would lead to social isolation or social interaction between the separately-placed students. The researchers give details of some of the numerous peer-to-peer interactions that occurred, many of which fall into the category of “hey look what I’m doing on my computer” type of interactions. Predictably, teachers had to sometimes give assistance to students, and also had to adjudicate arguments between students (Heft & Swaminathan, 2002). In reading through these anecdotal episodes, it occurs to me that these are the kinds of social interactions that take place when any toys are being played with in a preschool classroom; in this case, the toys just happen to be computer-based learning games.

The second socialization-oriented study was set in an inner-city preschool, and looked at the potential for computing technology to have a positive effect in mitigating the disruptive behavior of “at-risk” students, behaviors which included “poor attention to directions, hyperactivity, and aggression”. The researchers studied and compared two groups of young students, with one group working with computerized math games twice a week, and the other group not getting computer access. Their findings showed that the “at-risk” preschool students who found it difficult to sit still in a normal class would be quite attentive throughout a twenty to twenty-five minute session of computer-based math games. Not surprisingly, their performance on math assessments was noticeably better than that of their counterparts who were not given access to computers. However, the researchers noted that the disruptive behaviors of the “at-risk” students resumed seconds after they got back into their normal classroom (Laffey, et al, 2003).

Conclusions
No overarching conclusions can be derived from a cursory look at two studies, but I think it can be said that there is nothing in either study that would suggest that the usage of computers by preschool students would likely provide notable incremental benefits in the socialization of the children, either in peer-to-peer interactions or student-to-teacher interactions. The first study simply showed that computer learning games offer the same opportunities for social interaction and learning that any other “toy” in the classroom offers, and the second study shows that, while disruptive children are temporarily pacified by computer learning games, their behavioral problems are not permanently ameliorated in any identifiable way.

References:

Frede, E. & Ackerman, D. (2007). Preschool Curriculum Decision Making: Dimensions to Consider. Retrieved March 2, 2009 from http://nieer.org/resources/factsheets/19.pdf

Head Start New Castle County [Delaware] (2009). Curriculum. Retrieved, March 1, 2009 from http://www.ncchs.org/curriculum.html

Head Start Portland [Oregon] Public Schools (2009). Curriculum – Basic Educational Skills as Defined by Head Start. Retrieved, March 1, 2009 from http://www.headstart.pps.k12.or.us/.docs/pg/10207

Heft, T., & Swaminathan, S. (2002, March 1). The Effects of Computers on the Social Behavior of Preschoolers. Journal of Research in Childhood Education, 16(2), 162-74. (ERIC Document Reproduction Service No. EJ654377) Retrieved March 3, 2009, from ERIC database.

International School of Tianjin [IST] (2008). IST Curriculum Handbook. Retrieved, March 2, 2009 from http://www.istianjin.org/uploaded/documents/hndbk_crrclm_08_09.pdf

Laffey, J., Espinosa, L., Moore, J., & Lodree, A. (2003). Supporting Learning and Behavior of At-Risk Young Children: Computers in Urban Education. Journal of Research on Technology in Education, 35(4). Retrieved March 3, 2009, from https://www.msu.edu/~shubelro/researcharticle.pdf

Thompson, R. (2008). Connecting Neurons, Concepts, and People; Brain Development and its Implications. Retrieved, March 1, 2009 from http://nieer.org/resources/policybriefs/17.pdf

The Tendency to Neglect Questions of Efficiency in Educational Technology Research

Yet another paper that I submitted early this semester (Spring '09) at George Washington University...

In the course of completing many learning activities that take place in an elementary school classroom, there are usually some steps that could be referred to as constituting a kind of “clerical overhead”, duties and actions that fall outside of the explicit realm of students directly engaging in a learning activity. Clerical overhead accrues to both teachers and students, and some of it unquestionably constitutes an irreducible positive educational component in and of itself, such as a teacher grading a set of handwritten student essays (gathering vital formative assessment information) or students tracking their progress with the week’s homework on personal checklists. However, for both teachers and students, some clerical overhead represents something to be gotten out of the way as quickly as possible so that real teaching or learning activities can commence. Examples of such overhead might include: a teacher’s manual grading of multiple choice quizzes, or young students taking an inordinate amount of time to simply go around the room and gather supplies for an activity. For teachers, it is a zero-sum game: the more they can reduce the duration of such overhead tasks, the more time they can spend in high-quality lesson preparation and teaching with students. In my discussions with teachers this year, the most prevalent frustration expressed to me is that excessive administrative and clerical overhead undermines their ability to be effective teachers. While reduction of substantial parts of this overhead may not be addressable by educational computing technologies, some parts of it may well be.

A simple question that is often asked in industrial settings is, “Given that a task might be done with or without a specific technological toolset, what is the incremental time savings accrued through use of the toolset?” Within industry, such a time-oriented productivity analysis tends to be of prime importance and is rarely neglected. But in my very limited survey of educational computing research, I am finding questions such as this only indirectly addressed, if they are addressed at all. For example, a study on usage of handheld student-response devices (used peripherally with a popular interactive whiteboard system) focused on questions of student achievement and attitudes associated with usage of the devices (English, 2006). Besides offering a flawed, “apples and oranges” quantitative comparison to assess student achievement, the study failed to focus on questions of student/teacher productivity in usage of the devices. The comments from teachers that were included in the study hinted that there may have been significant savings of a teacher’s time when multiple-choice tests were administered to the class via the hand-held devices, and then instantly and automatically graded by the associated software installed on the teacher’s computer. How much time might be saved per week by a teacher that is facile with this technology, time that would not have to be spent sitting and grading objective tests, but that could instead be used for higher-level teaching tasks, such as explorations of advanced ways to differentiate lessons or to develop creative trans-disciplinary tie-ins? Not only did this study not consider the question, it also did not recommend that a future study look at the question. Are the authors unaware that such a question regarding possible reduction of “clerical overhead” might be asked, or is such a question deemed appropriate for industrial assembly lines but inappropriate for educational computing research?

To investigate further, I rather randomly stumbled into the current issue of the Journal of Educational Computing Research and reviewed an article on the hot topic of one-to-one computing in schools (Lei & Zhao, 2008). Since most schools that might be considering an “upgrade” to one-to-one computing likely already have computers (either present in the classroom or in separate computing labs), I expected that some of the study might focus on the incremental benefits that accrue to the students of a school in switching from a less-pervasive computing presence to a more-pervasive one. A part of such an analysis would almost surely focus on efficiencies afforded a student who no longer needs to reserve computer time or wait their turn to access a computer. Quite simply: How much more quickly would a student with their own notebook computer be able to accomplish certain basic computing tasks, as opposed to a student in a shared-computer situation? But once again, this study focused exclusively on questions of effectiveness of learning – certainly not a bad focus, but an incomplete focus, ignoring simple but potentially important questions of efficiency.

As mentioned above, the observations made here are based upon a very small sampling of educational computing research done over the course of my first three active weeks in the GWU ETL program. My intention is to use this focus paper as scaffolding for further investigations in the field of educational computing research, particularly focusing on the question of whether the exclusion of time-oriented productivity analysis is indeed widespread within the field, and whether any authorities in the field are in agreement with me in identifying this as a problem.

References/Influences:

English, Lauren J. (2006, September). ACTIVote: Can It Activate Our Students to Learn? Action Research Exchange, 5(2). Retrieved February 4, 2009, from
http://chiron.valdosta.edu/are/vol5no2/PDF/AREarticlesVol5no2/EnglishL-AREarticle-vol5no2.pdf

Labaree, David (1998, November). Educational Researchers: Living with a Lesser Form of Knowledge. Educational Researcher, 27(8). Retrieved January 22, 2009, from http://www.stanford.edu/~dlabaree/publications/Ed_Researchers_Living_with_Lesser.pdf

Lei, J., & Zhao, Y. (2008, January 1). One-to-One Computing: What Does It Bring to Schools? Journal of Educational Computing Research, 39(2), 97-122. (ERIC Document Reproduction Service No. EJ820002) Retrieved February 8, 2009, from ERIC database.

Newby, Timothy (2006). Educational Technology for Teaching and Learning. Upper Saddle River, NJ: Pearson Education, Inc.

Roblyer, M.D. (2006). Integrating Educational Technology in Teaching. Upper Saddle River, NJ: Pearson Education, Inc.

Woolfolk, Anita (2008). Educational Psychology. Boston: Pearson Education, Inc.