Preparing Tomorrow's Teachers to use Technology: learning and attitudinal impacts on elementary students.The research discussed in this manuscript manuscript, a handwritten work as distinguished from printing. The oldest manuscripts, those found in Egyptian tombs, were written on papyrus; the earliest dates from c.3500 B.C. was supported by a capacity building grant funded by the Department of Education as a Preparing Tomorrow's Teachers to use Technology Grant (PT3). The problem was to determine which instruction provided by teacher candidates provided the greatest learning and attitudinal gains for elementary school elementary school: see school. students. Pairs of teacher candidates were divided into three groups to provide instruction in one of three ways, (1) multimedia (HyperStudio), (2) Internet Internet Publicly accessible computer network connecting many smaller networks from around the world. It grew out of a U.S. Defense Department program called ARPANET (Advanced Research Projects Agency Network), established in 1969 with connections between computers at the , and (3) control which didn't did·n't Contraction of did not. didn't did not didn't do use technology to instruct in·struct v. in·struct·ed, in·struct·ing, in·structs v.tr. 1. To provide with knowledge, especially in a methodical way. See Synonyms at teach. 2. To give orders to; direct. v. elementary school students. Pre- and posttests designed to measure the learning and attitudinal gains were administered to all participating elementary school students. The instruction provided was focused on levers for one session and simple machines for the second session. A statistical analysis was made of the pre and posttests. Findings revealed significant differences between groups. ********** In the fall of 1980, five fifth grade students, the media coordinator, and school principal fixed their full attention on the teletype machine that had been purchased at the University of Utah The University of Utah (also The U or the U of U or the UU), located in Salt Lake City, is the flagship public research university in the state of Utah, and one of 10 institutions that make up the Utah System of Higher Education. as surplus equipment. We had connected to the U of U mainframe via a telephone line. We were anxiously waiting for the response to a question we had asked. This discarded dis·card v. dis·card·ed, dis·card·ing, dis·cards v.tr. 1. To throw away; reject. 2. a. To throw out (a playing card) from one's hand. b. machine began to shake and clatter clat·ter v. clat·tered, clat·ter·ing, clat·ters v.intr. 1. To make a rattling sound. 2. To move with a rattling sound: clattering along on roller skates. as the answer emerged; the expressions of those present told the simple story that education would never be the same. At first, this electronic magic only touched a few. Over the past twenty years TWENTY YEARS. The lapse of twenty years raises a presumption of certain facts, and after such a time, the party against whom the presumption has been raised, will be required to prove a negative to establish his rights. 2. expressions of that early experience have been duplicated again and again by people who have caught the vision of the how technology can support teaching and learning. A significant percentage of educators have always felt that computers could support and enhance learning opportunities in classrooms across the nation (Yildirim, 2000). But, as with other technological developments, schools have not been without naysayers who are reluctant to integrate technology, hoping computers would merely be a passing fad (Beck & Wynn, 1998; Duhaney, 2001). Personal computers are certainly not the teaching machines that were originally conceived. Today, we look to computers for instructional support. They can manage data, reinforce instructional concepts, act as resources for information in a random learning environment, promote multimedia concept learning that address multiple learning modes, and deliver on demand learning programs over multiple types of e-systems to name a few of the current and potential uses (Farnsworth Farns·worth , Philo Taylor 1906-1971. American electrical engineer who as early as 1927 demonstrated a working television system. & Wilkinson Noun 1. Wilkinson - English chemist honored for his research on pollutants in car exhausts (born in 1921) Sir Geoffrey Wilkinson , 1987; Shaw & Farnsworth, 1993). It is interesting to note that there is a continuous change in the use of computers as technology advances and new applications are created (Mize, 2000; Yildirim, 2000). As a result of research, we have learned that computers are extremely effective for some instructional applications and not effective for other instructional applications (Becker Beck´er n. 1. (Zool.) A European fish (Pagellus centrodontus); the sea bream or braise. , 2000; Shields, 2001). In the past, the idea of integrating technology into the regular classroom curriculum was a relatively weak component of teacher preparation (Yildirim, 2000). To respond to this challenge, a federal grant, Preparing Tomorrow' s Teachers to use Technology (PT3), provided resources to determine what teacher training institutions need to do to help teachers learn computer integration skills in order to increase the learning advantage for all students. This study summarizes results from the PT3 project in the Education Department at Utah Valley State College Utah Valley State College or UVSC, is a publicly-funded college located in Orem, Utah. Although the college has many courses of study, including an increasing number of bachelor's degree programs, it still retains many of its trade and technical school roots. . More specifically, what has been learned from the elementary students themselves. Problem As a part of the capacity building PT3 grant awarded to Utah Valley Utah Valley is a valley in North Central Utah located in Utah County, and is considered part of the Wasatch Front. It contains Provo, Orem, and their suburbs, including Spanish Fork and American Fork. Utah Lake is a natural shallow fresh water lake in its center. State Coruege in 1999 we were interested in studying the things that teachers needed to know to make a positive learning different for students. The problem was to determine which instruction provided by teacher candidates resulted in the greatest learning and attitudinal gains by elementary school students. Methods The study was conducted in two parts: Part 1: Levers, and Part 2: Simple Machines: Part 1: Levers The subjects consisted of 1,352 third, fourth, fifth, and sixth grade students in 31 classroom groups from nine suburban elementary schools in Utah. Each classroom group was instructed by one of 31 pairs of pre-service teacher candidates. Design. A pretest-posttest design with intact classroom groups was used. Teacher candidates instructed elementary students in their usual classroom groups. Each classroom group (hence elementary students) was assigned as·sign tr.v. as·signed, as·sign·ing, as·signs 1. To set apart for a particular purpose; designate: assigned a day for the inspection. 2. to one of three treatment groups: HyperStudio[R] (multi-media), Internet (technology-based search), or Control (no integrated technology). All elementary students were taught the same hands-on hands-on adj. Involving active participation; applied, as opposed to theoretical: "We're involved in hands-on operations, pulling levers, pushing buttons" Arthur R. Taylor. science lesson about levers, and were distinguished only by the technology-based activities (treatment group) used to reinforce the knowledge gained. Students in the HyperStudio[R] group were engaged in the creation of a multi-media presentation about levers using the HyperStudio[R] application (HyperStudio[R] Software, 1998). Students in the Internet group were engaged in technology-based search activities using selected Internet sites. Students in the control group described their hands-on experience in writing and with a diagram diagram /di·a·gram/ (di´ah-gram) a graphic representation, in simplest form, of an object or concept, made up of lines and lacking pictorial elements. . An instrument was created for assessing knowledge and attitudes among elementary students, both before (pretest pre·test n. 1. a. A preliminary test administered to determine a student's baseline knowledge or preparedness for an educational experience or course of study. b. A test taken for practice. 2. ) and after (posttest post·test n. A test given after a lesson or a period of instruction to determine what the students have learned. ) instruction (see Appendix A). The knowledge assessment portion consisted of 11 items about levers extracted from the district-approved science curriculum. All information reflected in the 11 items was covered in the instruction provided by the teacher candidates. The attitudinal portion of the instrument consisted of five items requiring student to self-report their attitudes on Likert scales Likert scale A subjective scoring system that allows a person being surveyed to quantify likes and preferences on a 5-point scale, with 1 being the least important, relevant, interesting, most ho-hum, or other, and 5 being most excellent, yeehah important, etc from 0 to 5 regarding the subject matter, technology, and the integration of technology for learning. Procedures. Teacher candidates accomplished instruction in two-person teams as a two-hour in-class activity. Part 2: Simple Machines The subjects consisted of 1,428 third, fourth, fifth, and sixth grade students in 31 intact classrooms from nine suburban elementary schools in Utah. The same 31 pairs of pre-service teacher candidates instructed them. Design. A pretest-posttest design with intact classroom groups was used. Teacher candidates instructed elementary students in their usual classroom groups. Each classroom groups (hence elementary students) were assigned to one of three treatment groups representing different means of technology integration: presentation (instructor delivered presentation only), Internet (technology-based search) and HyperStudio[R] (multimedia). Students in the presentation group were instructed in the content through a presentation provided by the corresponding teacher candidates. Students in the HyperStudio[R] group were instructed through a multi-media presentation using the HyperStudio[R] application. Students in the Internet group were engaged in technology-based search activities using selected Internet sites. Additionally, after instruction the teacher candidates reinforced the material learned through one of three reinforcement reinforcement /re·in·force·ment/ (-in-fors´ment) in behavioral science, the presentation of a stimulus following a response that increases the frequency of subsequent responses, whether positive to desirable events, or methods: discussion, demonstration or both. All elementary students were taught the same hands-on science lesson about simple machines, and were distinguished only by the means of technology integration (treatment group) used to and the subsequent reinforcement method employed. An instrument was created for assessing knowledge and attitudes among elementary students, both before (pretest) and after (posttest) instruction (see Appendix B). The knowledge assessment portion consisted of 19 items about simple machines extracted from the district-approved science curriculum. All information reflected in the 19 items was covered in the instruction provided by the teacher candidates. The attitudinal portion of the instrument consisted of five items requiting student to self-report their attitudes on Likert scales from 0 to 5 regarding the subject matter, technology, and the integration of technology for learning. Procedures. Teacher candidates accomplished instruction as two-person teams as a two-hour in-class activity. Results Part I: Levers Learning Impact: Acquisition of Knowledge. Table 1 and Figure 1 summarize sum·ma·rize intr. & tr.v. sum·ma·rized, sum·ma·riz·ing, sum·ma·riz·es To make a summary or make a summary of. sum results for Part I of the study regarding knowledge scores achieved by elementary student participants. Analysis of variance The discrepancy between what a party to a lawsuit alleges will be proved in pleadings and what the party actually proves at trial. In Zoning law, an official permit to use property in a manner that departs from the way in which other property in the same locality with repeated measures (Table 2) indicated that every group improved significantly between the pre and posttest occasions (F= 1715.1, df= 1, p=.000). Additionally, the ANOVA anova see analysis of variance. ANOVA Analysis of variance, see there (followed by a Scheffe post-hoc multiple comparison procedure) indicated that both the HyperStudio[R] and Internet groups performed significantly better than their Control counterparts on the posttest. [FIGURE 1 OMITTED] Attitudinal Impact. Table 3 and Figure 2 summarize results for Part I of the study regarding attitudes of elementary student participants. Analysis of variance with repeated measures (Table 4) indicated that the Internet and control group participants improved significantly between the pre and posttest occasions (F= 10.58, df= 1, p=.001), while the HyperStudio[R] group remained unchanged. [FIGURE 2 OMITTED] Additionally, the ANOVA (followed by a Scheffe post-hoc multiple comparison procedure) indicated that, although the Internet group scored significantly lower than either other group on the pre-test, that gap had closed by the posttest. Also, the control group experienced the significantly highest attitude ratings on the posttest when contrasted with either the HyperStudio[R] or the Internet groups, which did not differ significantly from each other. Part II: Simple Machines Learning Impact: Acquisition of Knowledge. Table 5 and Figure 3 summarize results for Part II of the study regarding knowledge scores achieved by elementary student participants. Analysis of variance with repeated measures (Table 6) indicated that every group improved significantly between the pre and posttest occasions (F= 242.54, df=1, p=.000). Additionally, the ANOVA (followed by a Scheffe post-hoc multiple comparison procedure) indicated that the presentation group performed significantly better than either the Internet or HyperStudio[R] groups on the posttest. [FIGURE 3 OMITTED] Analysis was also undertaken to discern dis·cern v. dis·cerned, dis·cern·ing, dis·cerns v.tr. 1. To perceive with the eyes or intellect; detect. 2. To recognize or comprehend mentally. 3. potential advantages to instructional approaches that simultaneously consider technology integration (presentation vs. Internet vs. HyperStudio[R]) as well as reinforcement methods utilized (demonstration vs. discussion vs. both). Teacher candidates were categorized cat·e·go·rize tr.v. cat·e·go·rized, cat·e·go·riz·ing, cat·e·go·riz·es To put into a category or categories; classify. cat as to which combination of technology integration and reinforcement method best described the instructional approach they used for presenting the material (e.g. Internet + discussion, presentation + demonstration). Review of the data revealed that seven instructional approaches were represented in the data. Table 7 and Figure 4 summarize results for posttest knowledge scores by instructional approach. A one-way one-way adj. 1. Moving or permitting movement in one direction only: a one-way street. 2. Providing for travel in one direction only: a one-way ticket. ANOVA (Table 8) showed that a significant difference existed among student scores according to according to prep. 1. As stated or indicated by; on the authority of: according to historians. 2. In keeping with: according to instructions. 3. the instructional approach utilized (F= 8.21, df=6, p=.000). Further analysis (Scheffe post hoc post hoc adv. & adj. In or of the form of an argument in which one event is asserted to be the cause of a later event simply by virtue of having happened earlier: multiple comparison procedure) indicated that elementary students in the presentation + discussion group combination experienced significantly higher posttest scores than did their counterparts in the Internet + both group - all other differences among instructional approaches were not statistically significant. [FIGURE 4 OMITTED] Attitudinal Impact. Table 9 and Figure 5 summarize results for Part II of the study regarding attitudes of elementary student participants. Analysis of variance with repeated measures (Table 10) indicated that attitude ratings increased significantly between occasions (pre versus post) for students in the presentation and HyperStudio[R] groups (F=7.30, df=1, p=.007), but not for students in the Internet group, which remained unchanged. No significant differences existed between groups on the posttest occasion for attitude ratings. [FIGURE 5 OMITTED] Table 11 and Figure 6 summarize results for posttest attitudinal scores by instructional approach. A one-way ANOVA (Table 12) showed that, while differences existed between approaches, none was statistically significant. [FIGURE 6 OMITTED] Conclusion Generally arguments in support of technology would suggest that by merely using technology student attitudes would be more positive. In both of these investigations just the opposite phenomena appeared to prevail. It could very well be that when technology is used and expectations are imposed on students that learning will increase because of the added instructional support elements but attitude will fall because of the new yet subtle pressure to perform with tools that are unfamiliar and have not been mastered. Additional studies are needed to confirm the results obtained. Longitudinal studies longitudinal studies, n.pl the epidemiologic studies that record data from a respresentative sample at repeated intervals over an extended span of time rather than at a single or limited number over a short period. would also help to determine if students gained in attitude as new skills are mastered. Appendix A LET'S let's Contraction of let us. FIND OUT WHAT YOU HAVE LEARNED ABOUT LEVERS. Your name -- Grade -- Date -- Your school -- Student Teachers' Names -- Write a name for each of the parts of the lever lever, simple machine consisting of a bar supported at some stationary point along its length and used to overcome resistance at a second point by application of force at a third point. The stationary point of a lever is known as its fulcrum. next to the numerals on the diagram [ILLUSTRATIONS OMITTED] 7. How does a lever make work easier? 8. What does work equal? 9. How does the amount of work done on the left side of the lever compare to the amount on the right side? 10. When the effort distance is greater than the load distance, how does the effort compare to the load? [ILLUSTRATION OMITTED] 11. When the effort distance is smaller than the load distance, how does the effort compare to the load? [ILLUSTRATION OMITTED]
SURVEY QUESTIONS
We are trying to see how you like learning about science.
Please answer the items below on a scale from 0 to 5.
0 is the lowest score.
5 is the highest score.
Please be honest. Circle your best answer.
Not All the
At All Time
1. I like learning about science 0 1 2 3 4 5
2. I am good at science 0 1 2 3 4 5
3. I like to do reports about science 0 1 2 3 4 5
4. It is important to learn science 0 1 2 3 4 5
5. Learning science is fun. 0 1 2 3 4 5
Appendix B Simple Machines POSTTEST [ILLUSTRATIONS OMITTED]
SURVEY QUESTIONS
We are trying to see how you like learning about science.
Please answer the items below on a scale from 0 to 5.
0 is the lowest score.
5 is the highest score.
Please be honest. Circle your best answer.
Not All the
At All Time
1. I like learning about science 0 1 2 3 4 5
2. I am good at science 0 1 2 3 4 5
3. I like to do reports about science 0 1 2 3 4 5
4. It is important to learn science 0 1 2 3 4 5
5. Learning science is fun. 0 1 2 3 4 5
Table 1.
Mean Knowledge Scores for Levers Participants by Group
Std.
Group Occasion Mean Deviation N
HyperStudio Pre-test 0.73 1.14 248
Posttest 5.99 2.81 245
Internet Pre-test 0.79 1.35 214
Posttest 5.81 2.73 218
Control Pre-test 0.71 1.21 225
Posttest 4.97 2.83 202
Table 2.
ANOVA for Knowledge Scores for Lever Participants
Source Sum of df Mean
Squares Square
Corrected Model 8169.418 5 1633.884
Intercept 13473.000 1 13473.000
Group 71.580 2 35.790
Occasion 7897.453 1 7897.453
Interaction Group x Occasion 59.802 2 29.901
Error 6197.881 1346 4.605
Total 27702.000 1352
Corrected Total 14367.299 1351
Source F Sig.
Corrected Model 354.832 .000
Intercept 2925.945 .000
Group 7.773 .000
Occasion 1715.098 .000
Interaction Group x Occasion 6.494 .002
Error
Total
Corrected Total
R Squared = .569 (Adjusted R Squared = .567)
Table 3.
Mean Attitudinal Scores for Levers Participants by Group
Std.
Group Occasion Mean Deviation N
HyperStudio[R] Pre-Test 3.55 1.03 240
Posttest 3.51 1.06 222
Internet Pre-Test 3.22 1.20 214
Posttest 3.55 1.19 196
Control Pre-Test 3.44 1.22 217
Posttest 3.78 1.11 194
Table 4
ANOVA for Attitudinal Scores for Lever Participants by Group
Source Sum of df Mean
Squares Square
Corrected Model 33.014 5 6.603
Intercept 15705.331 1 15705.331
Group 10.407 2 5.203
Occasion 13.632 1 13.632
Interaction Group x Occasion 10.193 2 5.096
Error 1645.354 1277 1.288
Total 17432.356 1283
Corrected Total 1678.367 1282
Source F Sig.
Corrected Model 5.125 .000
Intercept 12189.299 .000
Group 4.038 .018
Occasion 10.580 .001
Interaction Group x Occasion 3.955 .019
Error
Total
Corrected Total
R Squared = .020 (Adjusted R Squared = .016)
Table 5.
Mean Knowledge Scores for Simple Machines Participants by Group
Std.
Group Occasion Mean Deviation N
Presentation Only Pre-Test 8.87 3.32 222
Posttest 12.91 3.49 220
Internet Only Pre-Test 8.84 3.44 290
Posttest 11.87 3.23 279
HyperStudio(r) Only Pre-Test 9.45 3.18 110
Posttest 12.06 3.46 111
Table 6.
ANOVA for Knowledge Scores for Simple Machines Participants by Group
Source Sum of df Mean
Squares Square
Corrected Model 3569.955 5 713.991
Intercept 119872.749 1 119872.749
Group 75.349 2 37.675
Occasion 2742.048 1 2742.048
Interaction Group x Occasion 96.903 2 48.451
Error 13860.538 1226 11.305
Total 155981.000 1232
Corrected Total 17430.493 1231
Source F Sig.
Corrected Model 63.154 .000
Intercept 10603.051 .000
Group 3.332 .036
Occasion 242.541 .000
Interaction Group x Occasion 4.286 .014
Error
Total
Corrected Total
R Squared = .205 (Adjusted R Squared = .202)
Table 7.
Mean Knowledge Scores for Simple Machines Participants by
Instructional Strategy
N Mean Std. Deviation
Presentation + Discussion 46 13.37 3.63
Internet + Discussion 42 11.05 2.85
Presentation + Demonstration 151 12.95 3.64
Internet + Demonstration 89 13.36 2.89
HyperStudio(r) + 64 12.36 3.85
Demonstration
Presentation + Both 50 11.94 2.46
Internet + Both 117 10.80 3.35
Total 559 12.30 3.47
Table 8.
ANOVA for Knowledge Scores for Simple Machines Participants by
Instructional Strategy
Sum of Squares df Mean F Sig.
Square
Between Groups 551.685 6 91.947 8.210 .000
Within Groups 6181.825 552 11.199
Total 6733.510 558
Table 9.
Mean Attitudinal Scores for Simple Machines Participants by Group
Std.
Group Occasion Mean Deviation N
Presentation Only Pre-Test 3.41 1.06 203
Posttest 3.73 1.15 197
Internet Only Pre-Test 3.72 1.10 284
Posttest 3.73 1.25 266
HyperStudio(r) Only Pre-Test 3.61 1.07 90
Posttest 3.87 1.18 110
Table 10.
ANOVA for Attitudinal Scores for Simple Machines Participants by Group
Source Sum of df Mean
Squares Square
Corrected Model 20.993 5 4.199
Intercept 12976.118 1 12976.118
Group 6.654 2 3.327
Occasion 9.512 1 9.512
Interaction Group x Occasion 6.058 2 3.029
Error 1491.625 1144 1.304
Total 17023.330 1150
Corrected Total 1512.618 1149
Source F Sig.
Corrected Model 3.220 .007
Intercept 9952.017 .000
Group 2.552 .078
Occasion 7.295 .007
Interaction Group x Occasion 2.323 .098
Error
Total
Corrected Total
R Squared = .014 (Adjusted R Squared = .010)
Table 11.
Mean Attitudinal Scores for Simple Machines Participants by
Instructional Strategy
N Mean Std. Deviation
Presentation + Discussion 45 3.531 1.058
Internet + Discussion 42 3.817 1.430
Presentation + Demonstration 133 3.789 1.153
Internet + Demonstration 86 3.597 1.263
HyperStudio(r) + Demonstration 64 3.659 1.259
Presentation + Both 45 3.604 1.182
Internet + Both 108 3.864 1.219
Total 523 3.721 1.216
Table 12.
ANOVA for Attitudinal Scores for Simple Machines Participants by
Instructional Strategy
Sum of Squares df Mean F Sig.
Square
Between Groups 7.017 6 1.169 .789 .578
Within Groups 764.373 516 1.481
Total 771.390 522
References Abbott Ab·bott , Berenice 1898-1991. American photographer known especially for her series of black-and-white portraits of New York City. Abbott, George 1887-1995. , J. A., & Faris FARIS Firearms Research Information System , S. E. (2000). Integrating technology into preservice literacy instruction: A survey of elementary education elementary education or primary education Traditionally, the first stage of formal education, beginning at age 5–7 and ending at age 11–13. students' attitudes toward computers. Journal of Research on Computing computing - computer in Education, 33(2), 149. Beck, J.A. & Wynn, H.C. (1998). Technology in Teacher Education: Progress along the continuum Continuum (pl. -tinua or -tinuums) can refer to:
Becker, H. J. (2000). Findings from the teaching, learning, and computing survey: Is Larry Lar´ry n. 1. Same as Lorry, or Lorrie. Cuban right? Education Policy Analysis Archives Education Policy Analysis Archives is a peer-reviewed, open access scholarly journal created in 1993 by Gene V. Glass at Arizona State University. Articles are published in English, Spanish or Portuguese. , 8(51). Retrieved November November: see month. 2000 from the World Wide Web: http://epaa.asu.edu/epaa/ v8n51 Duhaney, D. C. (2001). Teacher Education: Preparing teachers to integrate technology. International Journal of Instruction Media, 28(1), 23. HyperStudio[R] Software for a Mediacentric World: Tutorial An instructional book or program that takes the user through a prescribed sequence of steps in order to learn a product. Contrast with documentation, which, although instructional, tends to group features and functions by category. See tutorials in this publication. . (1987). El Cajon El Cajon (ĕl kähōn`), city (1990 pop. 88,693), San Diego co., S Calif.; inc. 1912. Electronic equipment, aircraft parts, irrigation equipment, furniture, and men's suits are among its manufactures. , CA: Roger Wagner Roger Wagner (January 16, 1914 - September 17, 1992) was a driving force in choral music, one of the giants who for five decades championed and refined the art and propelled it forth around the world. His musical and personal impact was profound. Publishing Inc. Farnsworth, B.J. & Wilkinson, J.C. (1987). A fully integrated management system for tracking mastery. T.H.E (operating system) T.H.E - The operating system in which semaphores were first used. . Journal, 15, 96-100. McKinnon McKinnon can refer to: People
a chronological study in epidemiology which attempts to establish a relationship between an antecedent cause and a subsequent effect. See also cohort study. of student attitudes toward computers: Resolving an attitude decay The reduction of strength of a signal or charge. decay - [Nuclear physics] An automatic conversion which is applied to most array-valued expressions in C; they "decay into" pointer-valued expressions pointing to the array's first element. paradox paradox, statement that appears self-contradictory but actually has a basis in truth, e.g., Oscar Wilde's "Ignorance is like a delicate fruit; touch it and the bloom is gone. . Journal of Research on Computing in Education, 32(3), 325. Mize, C. D., & Gibbons Famous people named Gibbons include:
The definition of instructional technology prepared by the Association for Educational Communications and Technology (AECT) Definitions and Terminology to support student learning in K-12 schools. In Society for Information Technology & Teacher Education International Conference: ED344 563. Proceedings of SITE 2000 (11th, San Diego, California “San Diego” redirects here. For other uses, see San Diego (disambiguation). San Diego is a coastal Southern California city located in the southwestern corner of the continental United States. As of 2006, the city has a population of 1,256,951. , February February: see month. 8-12, 2000) (pp. 2034-2037). Owens Owens, river, c.120 mi (190 km) long, rising in the Sierra Nevada, E Calif., SE of Yosemite National Park and flowing SE, to enter Owens Lake, near Mt. Whitney. Since 1913, at a point c. , C. H., Magoun, A. D., & Anyan, J. (2000). The effects of technology on the attitude of classroom teachers (E-TACT). In Society for Information Technology & Teacher Education International Conference: ED 444 531. Proceedings of SITE 2000 (11th, San Diego, California, February 8-12, 2000) (pp. 1528-1533). Shaw, H., and Farnsworth, B.J. (1993). The Academy of Multimedia: A quest for Verb 1. quest for - go in search of or hunt for; "pursue a hobby" quest after, go after, pursue look for, search, seek - try to locate or discover, or try to establish the existence of; "The police are searching for clues"; "They are searching for the new destinations. T.H.E. Journal, 20, 87-88. Shields, C. (2001). Curriculum fusion. Curriculum Administrator, 37(5), 50. Yildirim, S. (2000). Effects of an educational computing course on preservice and inservice teachers: a discussion and analysis of attitudes and use. Journal of Research on Computing in Education, 32(4), 479. Briant J. Farnsworth, Dean, School of Education; Steven Ste´ven n. 1. Voice; speech; language. Ye have as merry a steven As any angel hath that is in heaven. - Chaucer. 2. An outcry; a loud call; a clamor. To set steven to make an appointment. H. Shaha, Statistics Consultant; Damon Da·mon n. A legendary figure who, out of devotion, pledged his life as a guarantee that his condemned friend Pythias would return to face execution. Both were subsequently pardoned. Noun 1. L. Bahr, Assistant Professor; Valerie Name Valerie is a common name for a girl in both English and French. Spelt as "Valery" or "Valeri", it is a common male name in parts of Europe (particularly in France and Russia). It means brave and courageous. K. Lewis, Grant Researcher; and Linda A set of parallel processing functions added to languages, such as C and C++, that allows data to be created and transferred between processes. It was developed by Yale professor David Gelernter, when he was a 23-year old graduate student. F. Benson, Department Chair of Elementary Education, Utah Valley State College. Correspondence concerning this article should be addressed ot Dr. Briant J. Farnsworth, Dean of Education, 800 West University Parkway, Orem, UT 84058-5999. |
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