Printer Friendly

Measuring the relationship between agriculture teachers' self-efficacy, outcome expectation, interest, and their use of interactive whiteboards.

Introduction

"Here and across the country, the traditional chalkboards that have been teachers' primary tool for presenting content for more than two centuries are quickly being erased from classrooms" (Manzo, 2010, para. 3). This phenomenon is due partly to meet the needs of the digital generation (Manzo, 2010). Students of today have changed drastically and are not the students our current educational system was intended to teach (Oblinger, 2003; Prensky, 2001; Tapscott, 1998). Contemporary students spend numerous hours interacting with computers, cellular phones, MP3 players, and a variety of other technologies (Bennett, Maton, & Kervin 2008; Prensky, 2001). As a result of this digital environment, and the absolute quantity of student interaction with technologies, students think and process information differently than previous generations (Brown, 2000; Frand, 2000; Prensky, 2001; Tapscott, 1999).

Prensky (2001) identified these modern day students as digital natives because students are native speakers of the language regarding digital technologies. Moreover, technological advances unfamiliar to prior generations of learners are routine with today's computer savvy generation (Bunch, Haynes, Ramsey, Edwards, & Robertson, 2010). Digital natives perceive that the educational system has brought in outsiders to instruct them. These students speak a different language than their pre-digital instructors (Prensky, 2001). Brown (2000) described this phenomenon as a shift in learning. He contributed this shift to differences in learning medium, i.e., Internet versus books. Digital natives have been engrossed with digital libraries and endless amounts of information via the Internet. As such, digital natives have also shifted from an authority-based learning style (i.e., behaviorist) to a more discovery-based learning style (i.e., constructivist) (Brown). Digital natives favor learning through investigation and trial. This is contrary to their pre-digital instructors who have a propensity to be authority-based. Prensky defined these pre-digital instructors as digital immigrants. A digital immigrant is someone who was not immersed in the digital world while growing up but has taken up using some aspects of digital technologies later in life.

As instructors who are digital immigrants confront the challenges that accompany a newfangled generation of students, they must reevaluate their approaches to instruction and recognize practices that are pertinent to today's digital natives (McAlister, 2009). One technological advancement being used in today's classrooms is the Interactive Whiteboard (IWB). Lewin, Somekh, and Steadman (2008) described IWBs as oversized, touch screen whiteboards coupled to a classroom computer, which allow teachers to access motionless and moving imagery accompanied by sound. IWBs offer a multi-media approach that addresses the needs of entire classes or individual learners, and are being used to challenge students to think by using an assortment of stimuli (i.e., audio, visual, and kinesthetic; Glover, Miller, Averis, & Door, 2007). Haldane (2007) noted that several interactivities were observed when teachers used IWBs. These interactivities included,
   Verbal interpersonal [communication]
   between the pupils and their teacher; Visual
   interaction between the pupils and the pictorial
   symbols on the IWB; Cognitive
   interaction between the pictorial symbols on
   the IWB; Teacher interaction with the
   content (verbal and on the IWB) and the
   pupil responses; Interactions with the
   content via the technological facility of the
   medium zoom in, to move parts of a plant
   around, to illustrate points by introducing
   short animations showing how a shoot
   grows up and a root grows down. (p. 269)


To that end, Hodge and Anderson (2007) asserted that student engagement (interactivity) is a positive element of teachers using IWBs.

The use of IWBs in the agricultural education classroom, due to its potential for stimulating interactivity, can be associated with experiential learning. Rufus Stimson (1919) surmised that, "neither skill nor business ability can be learned from books alone, nor merely from observation of the work and management of others. Both require active participation during the learning period . . ." (p. 32). More recent, Roberts (2006) noted that experiential learning has been a hallmark of secondary agricultural education. So, can IWBs be used as a tool to enrich experiential learning in secondary agricultural education?

Few studies have examined how agricultural education teachers are incorporating technology into their pedagogical practices (Kotrlik, Redmann, & Douglas, 2003). Given that little research has been conducted on how teachers are using IWBs, especially in the agricultural education classroom, a study examining agricultural education teachers' use of IWBs was warranted (Bunch et al., 2010). In particular, studies to describe teachers' self-efficacy regarding their use of IWBs could add value to the scholarly literature with implications for teacher professional development.

Theoretical Framework

The theoretical framework undergirding this study was Bandura's (1977) self-efficacy theory. According to Bandura (1977), two main influences on human behavior operate concurrently: an individual's personal characteristics and his or her environment. How the two interact independently with an individual's behavior, and with one another, influences a person's future behavior choices (Bandura, 1986). To change a behavior, the person needs to believe he or she is capable of performing the desired change and concomitant action (Bandura, 1989). Bandura referred to this concept as self-efficacy. Bandura (1993) noted that efficacy influences the way in which individuals feel, think, are motivated, and behave. Further, Bandura (1997) asserted that perceived self-efficacy is an individual's belief in his or her ability to systematize and perform the sequence of actions necessary to complete a task or achieve an outcome.

In addition, Bandura (1977) described the concept of outcome expectancy as a person's belief that a specific behavior will presage a definite outcome. Outcome expectations play a vital role in human motivation (Niederhauser & Perkman, 2008). If individuals do not believe their actions will have the preferred outcomes, they will be less likely to perform those actions (Pajares, 2006). Further, outcome expectations could make people maintain behaviors over time if they perceive their actions will produce the preferred outcome ultimately (Niederhauser & Perkman).

Self-efficacy and outcome expectations have a prevailing influence on interest (Lent et al., 2005; Smith, 2002). Demonstrations of interest replicate "a person's patterns of likes, dislikes, and indifferences regarding ... career relevant activities" (as cited in Niederhauser & Perkman, 2008, p. 101). According to Bandura (1986), people build interests in which they believe themselves to be self-efficacious and envision more positive outcomes. Likewise, in a study conducted by Fouad and Smith (1996), interest was a significant mechanism in career psychology, and a strong predictor of intentions.

Based on Bandura's (1977) self-efficacy theory, Tschannen-Moran, Hoy, and Hoy (1998) defined teacher self-efficacy as "the teacher's belief in his or her capability to organize and execute courses of action required to successfully accomplish a specific teaching task in a particular context" (p. 233). In addition, the combination of a teachers' perceptions of his or her teaching capability and beliefs about the task requirements contribute to teacher efficacy (Tschannen-Moran et al., 1998). The authors also posited that higher levels of efficacy presages more effort and perseverance, resulting in higher efficacy levels, and lower efficacy foretells less effort and perseverance leading to lower efficacy levels and poor teaching outcomes. This "fulfilling" or concomitant nature of self-efficacy in teaching also has been found in agricultural education (Knobloch, 2001; Roberts, Harlin, & Briers, 2008; Roberts, Harlin, & Ricketts, 2006; Whittington, McConnell, & Knobloch, 2006). However, the amount of research featuring teacher self-efficacy and its relationship to teachers' use of educational technologies in agricultural education is limited.

Purpose and Objectives

The purpose of this descriptive-correlational study was to assess selected perceptions (i.e., level of self-efficacy, outcome expectation, and interest) of Oklahoma secondary agricultural education teachers regarding their use of the IWB in classroom teaching. The study also sought to determine if relationships existed between teachers' IWB self-efficacy scores, outcome expectation scores, interest scores, and selected personal and professional characteristics.

Four research questions guided this study: (a) What were the selected personal and professional characteristics of Oklahoma agricultural education teachers, e.g., age, years of teaching experience, access to IWBs, access to IT personnel, and frequency of IWB use?; (b) What were Oklahoma agricultural education teachers' levels of self-efficacy, outcome expectation, and interest regarding the use of IWBs?; (c) What relationships existed between Oklahoma agricultural education teachers' self-efficacy, outcome expectation, and interest?; (d) What selected relationships existed between Oklahoma agricultural education teachers' levels of self-efficacy, outcome expectation, interest, and selected personal and professional characteristics.

Methods

The study presented here was descriptive and correlational; its target population consisted of Oklahoma secondary agricultural education teachers (N = 437) during the 2010-2011 academic year. The study's sample (n = 205) was selected randomly from the target population (Krejcie & Morgan, 1970). Data were collected through an Internet questionnaire using the Tailored Design Method developed by Dillman, Smyth, and Christian (2009). This process included four contacts by electronic mail during the fall semester of the 2010-2011 academic year.

To address frame error, i.e., teachers no longer in the profession and teacher relocation, 18 participants were removed from the sample. In addition, 18 participants had unusable electronic mail addresses resulting in their removal from the sample. So, the initial sample of 205 teachers was adjusted to an accessible sample of 169 teachers. Completed questionnaires were received from 81 of the 169 teachers for a 48% response rate. To ensure that results were representative of the target population, an independent samples t-test was used to compare early and late respondents (Lindner, Murphy, & Briers, 2001). The first one-half of respondents, as determined by the date of return of the instrument, were considered early and the later one-half of respondents formed the late group. Level of significance was set at p < .05 a priori. No statistically significant differences were found between early and late respondents for constructs representing the study's dependent variables (i.e., SE, OE, and INT; see Table 1). So, assuming the late respondents were similar to non-respondents, the results of this study were deemed representative of the target population regarding the variables of interest.

Instrumentation

The Interpersonal Technology Integration Scale (ITIS) developed by Niederhauser and Perkmen (2008) was used in this study. The 21-item ITIS asked teachers to signify their level of agreement with each statement using a fivepoint, summated-rating scale: 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, and 5 = strongly agree. The real limits of the scale were 1.00 to 1.49 = strongly disagree, 1.50 to 2.49 = disagree, 2.50 to 3.49 = neutral, 3.50 to 4.49 = agree, and 4.50 to 5.00 = strongly agree. The ITIS consisted of three constructs: Self-Efficacy (SE) to determine teachers' confidence for using IWBs (six items); Outcome Expectation (OE) to determine teachers' expected benefits from using IWBs (nine items); and Interest (INT) to determine teachers' interest in using IWBs (six items).

The ITIS was adjusted to meet the objectives of this study. Items were combined into a single instrument, which employed a five-point, summated-rating scale. Additionally, 18 professional and personal characteristics questions were added to describe the sample and make selected correlational analyses possible. The instrument was reviewed by a panel of four agricultural education experts at Oklahoma State University to establish content and face validity. Per the recommendations of the panel, minor revisions were made to the final instrument. The ITIS was then pilot-tested with 36 Oklahoma agricultural education teachers to determine reliability estimates by construct. Reliability analysis of the pilot instrument yielded acceptable Cronbach's alpha coefficients for the three constructs: SE = 0.93; OE = 0.91; INT = 0.89.

Data Analysis

The data collected were analyzed using SPSS[R] version 17.0 for Windows[TM]. Responses were coded for computer analysis. Research objectives one and two were analyzed using descriptive statistics (i.e., frequencies, percentages, means, and standard deviations). Research objectives three and four were achieved by computing Spearman rho and Pearson product-moment correlation coefficients, where appropriate. According to Ary, Jacobs, and Razavieh (2002), Pearson r offers a significant index for demonstrating relationships. The strength of relationships was described using Davis' (1971) coefficient conventions: .01 [greater than or equal to] r [greater than or equal to] .09 = Negligible, .10 [greater than or equal to] r [greater than or equal to] .29 = Low, .30 [greater than or equal to] r [greater than or equal to] .49 = Moderate, .50 [greater than or equal to] r [greater than or equal to] .69 = Substantial, and r [greater than or equal to] .70 = Very Strong.

Findings/Results

Research question one sought to describe selected personal and professional characteristics of Oklahoma agricultural education teachers. Seventy-three (90.1%) of the participants were male, eight (6.2%) were female, and three (3.7%) failed to respond (see Table 2). Five (6.2%) of the teachers were between 21 and 25 years of age, 18 (22.2%) of the respondents were between 26 and 30 years of age, 12 (14.8%) were between 31 and 35 years of age, and 14 (17.3%) were 51 years of age or older.

Regarding level of education attainment, a majority (70.4%) of the participants had earned a bachelor's degree only, and nearly one-fourth (24.7%) had earned a master's degree (see Table 2). Concerning years of teaching experience, 21 (25.9%) of the respondents indicated they had zero to five years of teaching experience, 16 (19.8%) had taught 11 to 15 years, and 14 (17.3%) had taught 6 to 10 years. Seventy-four teachers (91.4%) had received traditional teaching certification, and five (6.2%) indicated they had received their teaching certification via an alternative route. As for the size of school, most of the respondents indicated they were employed at either 1A schools (150 to 199 students), 2A schools (200 to 320 students), or B schools (86 to 149 students). The class size with the fewest respondents was class 5A (688 to 1242 students), where only two teachers (2.5%) reported being employed (see Table 2).

In all, 59 (72.8%) participants indicated having access to IWBs. Thirty-three (40.7%) participants reported having "full access" to school-employed IT personnel, 30 (37%) indicated having access to school-employed IT personnel "sometimes," and 10 teachers (12.3%) had no access to school-employed IT personnel (see Table 2).

Research question two sought to describe Oklahoma agricultural education teachers' level of self-efficacy, outcome expectation, and interest regarding the use of IWBs. Data are reported using summated means by item and construct (see Table 3).

When self-efficacy items were analyzed, respondents agreed that they were confident incorporating IWBs appropriately into lessons to enhance student learning (M = 3.93, SD = .83), and the respondents agreed they were confident teaching relevant subject matter with appropriate use of IWBs (M = 3.90, SD = .88) (see Table 3). In addition, the respondents agreed they could use IWBs effectively in their teaching (M = 3.89, SD = .82). The respondents reported having the lowest level of agreement in being confident about helping students when they have difficulties with IWBs (M = 3.49, SD = .94). In addition, responses to all self-efficacy items were summed and averaged to yield an overall self-efficacy score of 3.76 (SD = .76), indicating that the teachers agreed to being self-efficacious at using IWBs (see Table 3).

As for teachers' levels of agreement regarding outcome expectation, the respondents rated the item, using IWBs in the classroom will increase their effectiveness as a teacher, highest (M = 4.17, SD = .83) (see Table 3). The teachers expressed the second highest level of agreement with the item, using IWBs in the classroom will make their teaching more exciting (M = 4.11, SD = 1.00), and the third highest level of agreement was with the item, using IWBs in the classroom will increase my productivity (M = 4.02, SD = .88). However, the respondents were neutral regarding the item, effectively using IWBs in the classroom will increase their status among colleagues (M = 3.23, SD = .94). The responses to all outcome expectation items were summed and averaged, which yielded an overall outcome expectation score of 3.73 (SD = .72), indicating the teachers agreed that using IWBs would result in the learning outcome they intended to attain (see Table 3).

Regarding interest, the respondents' highest levels of agreement were with the items, I am interested in learning about new educational software (M = 4.11, SD = .76), and I am interested in working with IWB tools (M = 4.07, SD = .70) (see Table 3). The respondents indicated they were least interested in the item, I have an interest in reading articles or books about IWBs (M = 3.16, SD = .94). The responses to all interest items were summed and averaged, which yielded an overall interest score of 3.74 (SD = .68), indicating the teachers agreed that they were interested in using IWBs in their classroom teaching (see Table 3).

Research question three sought to describe selected relationships between Oklahoma agricultural education teachers' self-efficacy, outcome expectation, and interest regarding the use of IWBs. Outcome expectation and interest were related moderately and positively (r = .61), and had the highest correlation coefficient for the associations measured (see Table 4).

In addition, teachers' self-efficacy and outcome expectation regarding their use of IWBs was also related moderately and positively (r = .54). Teachers' self-efficacy and interest regarding IWB use revealed a low and positive relationship (r = .26) (see Table 4).

Research question four sought to describe relationships between Oklahoma agricultural education teachers' levels of self-efficacy, outcome expectation, and interest with selected personal and professional characteristics (i.e., age, years of completed teaching experience, size of school where employed, access to IWBs, access to school-employed IT personnel, and frequency of IWB use per week).

The analyses revealed that teachers' age, years of teaching experience, and size of school all had inverse relationships with the variables self-efficacy, outcome expectation, and interest (see Table 5). However, only the relationships between age, years of teaching experience, self-efficacy, and outcome expectation were statistically significant (p < .05). Self-efficacy and outcome expectation had a low and negative relationship with teacher age ([r.sub.s] = -.29). Self-efficacy ([r.sub.s] = -.26) and outcome expectation ([r.sub.s] = -.24) both demonstrated a negative and low relationship with a respondent's years of teaching experience (see Table 5). The teachers who were younger and had fewer years of teaching experience perceived they were more efficacious regarding their use of IWBs and held a higher outcome expectation for that practice.

In addition, teacher self-efficacy was found to be related moderately and positively with their access to IWBs ([r.sub.s] = .32), access to IT personnel ([r.sub.s] = .46), and IWB use per week ([r.sub.s] = .42) (see Table 6). The variable "outcome expectation" had a low and positive relationship with teachers' access to IT personnel ([r.sub.s] = .25) and their IWB use per week ([r.sub.s] = .23). However, teacher interest was not related significantly with the variables measured. The variable self-efficacy and access to IT personnel revealed the strongest relationship ([r.sub.s] = .46) (see Table 6).

Conclusions

The most frequent age category reported by the respondents was 26 to 30 years. As such, it can be concluded that the teachers in this group were born between 1980 and 1984. According to Bennett, Maton, and Kervin (2008), individuals born during or after 1980 are considered digital natives who prefer to use digital technology. Of the 81 respondents involved in this study, more than 90% were male. This finding is consistent with the Oklahoma agricultural education teacher population (G. Shoulders, personal communication, September 22, 2010). A majority of teachers had taught between zero (i.e., a first year teacher) and 15 years, and 63% were employed at smaller, more rural schools, ranging from class C (< 86 students) to class 2A (200 to 320 students). Nearly, three-fourths of the respondents had access to IWBs, and almost 80% had access to school-employed IT personnel at least sometimes (see Table 2).

This study revealed the responding teachers were confident using IWBs to teach and they perceived that IWBs enhanced student learning. In addition, the teachers indicated that IWBs made them more effective and their teaching more exciting. The findings also revealed teachers had an interest in learning about other educational technologies.

Small differences existed in the composite mean scores for the study's major constructs. The teachers agreed with the self-efficacy items (M = 3.76) regarding their use of IWBs. Teachers also "agreed" that IWBs would assist them in obtaining their outcome expectations regarding its use (M = 3.73). Finally, the teachers agreed that they were interested in IWBs (M = 3.74).

The findings of this study suggest that as a teacher's age and years of teaching experience increased, his or her levels of self-efficacy and outcome expectation regarding IWB use decreased. Therefore, younger and less experienced teachers were more efficacious and had higher expectations regarding their use of IWBs. This finding resonates with research by Prensky (2001) who claimed that most teachers, i.e., those who are older and more experienced, are digital immigrants and lack technological confidence. In addition, teachers who had access to IWBs agreed they were more efficacious because of opportunities to practice using the IWB. This finding is consistent with Bandura's (1977) self-efficacy theory, which posits the more an individual attempts a task, the more self-efficacious that person becomes regarding the behavior.

Further, this study showed that teachers who used IWBs more frequently perceived they held higher levels of self-efficacy and outcome expectation. This finding also supports research by Bandura (1989) who stated that to change a behavior (i.e., increased use of IWBs), an individual must believe he or she is capable of performing the task. In addition, this finding supports research by Pajares (2006) who claimed that if an individual perceives his or her actions will result in the preferred outcome, he or she is more likely to perform said actions. It should be noted that teacher interest was not found to be related significantly with any of the selected personal and professional characteristics tested. This finding contradicts research by Lent et al. (2005) and Smith (2002) who stated that self-efficacy and outcome expectation is likely to influence an individual's interest significantly.

Discussion and Implications

This study found two distinct teacher groups: digital immigrant teachers and digital native teachers. In terms of respondents, 72% were considered digital immigrants and 28% were digital natives. Teachers' ages and years of teaching experience were related negatively to outcome expectation for using IWBs. Further, it can be implied that because these veteran teachers are pre-digital (Prensky, 2001), it will take them longer to develop confidence in using IWBs, teaching with IWBs, and perceiving the relevance of IWBs, as indicated by their lower self-efficacy scores. Although the more experienced teachers did not use IWBs as frequently as less experienced teachers, Prensky (2001) noted digital immigrants used some aspects of digital technologies. The findings of this study supported Bandura's (1977) self efficacy theory which posits the more an individual attempts a task the more self-efficacious that person becomes.

Further, according to Bandura (1986), people develop interest in tasks for which they believe themselves to be efficacious. However, this study did not support that contention: Why is that? Teachers indicated having the highest level of agreement in learning about new educational technologies. So, could it be they have lost interest in using IWBs because new classroom technologies have been implemented? Or, could it be that IWBs are less novel than they once were, considering 73% of the teachers indicated having access to them (see Table 2).

Recommendations for Practice

Professional development opportunities should be created for teachers to learn how to use IWBs effectively to engage students better. In addition, providers of professional development should consider delivering workshops or in-service sessions designed to meet the needs of the two teacher groups: digital natives and digital immigrants. Opportunities should also exist in which digital native and digital immigrant teachers could be paired together to develop a Community of Practice (CoP) (Lave & Wenger, 1991). For example, a CoP devoted to learning about the use of IWBs and other instructional technologies could be formed. Teacher educators might consider using digital immigrants as cooperating teachers during the student teaching internship. Student teachers who are confident using IWBs could be placed purposefully with digital immigrant cooperators to create an environment where IWBs are used more frequently (Understandably, teacher educators must consider other important variables regarding a student teacher's placement, and, in some cases, a potential cooperator may excel the intern in his or her instructional technology acumen.).

Recommendations for Future Research

Future research should be conducted to determine which interactive technologies experienced and early-career teachers are using in their classrooms. This would provide insight on these teachers' needs regarding their use of instructional technologies. For example, are younger, less experienced teachers using IWBs in behavioral or constructivist ways (Brown, 2002)? In addition, future research should examine teachers' different types of interest more thoroughly in regard to an array of educational technologies, including IWBs. Finally, future inquires should be conducted to determine how the use of IWBs and other educational technology affects student learning and achievement in secondary agricultural education.

10.5032/jae.2012.01067

References

Ary, D., Jacobs, L. C., & Razavieh, A. (2002). Introduction to research in education. Belmont, CA: Wadsworth/Thomson Learning.

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215. doi: 10.1037/0033-295x.84.2.191

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.

Bandura, A. (1989). Human agency in social cognitive theory. American Psychologist, 44(10), 11751184. doi: 10.1037/0003-066x.44.9.1175

Bandura, A. (1993). Perceived self-efficacy in cognitive development and functioning. Educational Psychologist, 28(2), 117-148. doi: 10.1207/s15326985ep2802_3

Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: W.H. Freeman and Company.

Bennett, S., Maton, M., & Kervin, L. (2008). The 'digital natives' debate: A critical review of the evidence. British Journal of Educational Technology, 39(5), 775-786. doi: 10.1111/j.1467 8535.2007.00793.x

Brown, J. S. (2000). Growing up digital: How the web changes work, education, and the ways people learn. United States Distance Learning Association Journal, 16(2). Retrieved from http://www.usdla.org/html/journal/FEB02_Issue/article01 .html

Bunch, J. C., Whisenhunt, J. H., Edwards, M. C., Robinson, J. S., & Ramsey J. W. (2010, February). Using interactive whiteboards in the agricultural education classroom: How student teachers are using this technology--Potential implications for teacher educators. Poster presented at the 2010 AAAE Southern Region Conference, Orlando, FL. Abstract retrieved from http://aaaeonline.org/uploads/allconferences/2-5-2010_130_Final_Proceedings.pdf

Bunch, J. C., Whisenhunt, J. H., Ramsey J. W., Edwards, M. C., & Robertson, T. (2010, April). Making learning meaningful for the millennials: Podcasting with a purpose in agricultural education. Poster presented at the 2010 AAAE Western Region Conference, Great Falls, MT. Abstract retrieved from http://aaaeonline.org/uploads/allconferences/4-1 2010_796_2010_WR_AAAE_Poster_Proceedings2.pdf

Davis, J. A. (1971). Elementary survey analysis. Englewood Cliffs, NJ: Prentice-Hall.

Dillman, D. A., Smyth, J. D., & Christian, L. M. (2009). Internet, mail, and mixed-mode surveys: The tailored design method. Hoboken, NJ: John Wiley & Sons, Inc.

Fouad, N. A., & Smith, P. L. (1996). A test of a social cognitive model for middle school students: Math and science. Journal of Counseling Psychology, 43(3), 338-346. doi: 10.1037/00220167.43.3.338

Frand, J. (2000). The information-age mindset: Changes in students and implications for higher education. EDUCAUSE Review, 35, September-October, 14-24.

Glover, D., Miller, D., Averis, D., & Door, V. (2007). The evolution of an effective pedagogy for teachers using the interactive whiteboard in mathematics and modern languages: An empirical analysis from the secondary sector. Learning, Media and Technology, 32(1), 5-20. doi: 10.1080/17439880601141146

Haldane, H. (2007). Interactivity and the digital whiteboard: Weaving the fabric of learning. Learning, Media and Technology, 32(3), 257-270. doi: 10.1080/17439880701511107

Hodge, S., & Anderson, B. (2007). Teaching and learning with an interactive whiteboard: A teacher's journey. Learning, Media and Technology, 32(3), 271-282. doi: 10.1080.17439880701511123

Knobloch, N. A. (2001, December). The influence of peer teaching and early field experience on teaching efficacy beliefs of preservice educators in agriculture. Paper presented at the 2001 AAAE National Conference, New Orleans, LA. Abstract retrieved from http://aaaeonline.org/allconferences1.php?show_what=National&sorter_conf=National&sorter_year=2001

Kotrlik, J. W., Redmann, D. H., & Douglas, B. B. (2003). Technology integration by agriscience teachers in the teaching/learning process. Journal of Agricultural Education, 44(3), 78-90. doi: 10.5032/jae.2003.0378

Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607-610. doi: 10.1177/001316447003000308

Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. New York, NY: Cambridge Press.

Lent. R. W., Brown, S. D., Sheu, H., Schmidt, J., Brenner, B. R., Gloster, C. S., . . . Treistman, D. (2005). Social cognitive predictors of academic interests and goals in engineering: Utility for woman and students at historically black universities. Journal of Counseling Psychology, 52(1), 84-92. doi: 10.1037/0022-0167.52.1.84

Lewin, C., Somekh, B., & Steadman, S. (2008). Embedding interactive whiteboards in teaching and learning: The process of change in pedagogic practice. Education Information Technology, 13, 291-303. doi: 10.1007/s10639-008-9070-z

Lindner, J. R., Murphy, T. H., & Briers, G. E. (2001). Handling nonresponse in social science research. Journal of Agricultural Education, 42(4), 43-53. doi: 10.5032/jae.2001.0443

Manzo, K. (2010). Whiteboards' impact on teaching seen as uneven. Beyond Teacher Chalk Talk: Education Week's Digital Directions. Retrieved from http://www.edweek.org/dd/articles2010/01/08/02whiteboards.h03 .html

McAlister, A. (2009). Teaching the millennial generation. American Music Teacher, 59(1), 13-15. Retrieved from http://search.ebscohost.com.ezproxy.osu tulsa.okstate.edu/login.aspx?direct=true&db=aph&AN=43802552&site=ehost-live

Niederhauser, D. S., & Perkman, S. (2008). Validation of the intrapersonal technology scale: Assessing the influence of intrapersonal factors that influence technology integration. Computers in the Schools, 25(1), 98-111. doi: 10.1080/07380560802157956

Oblinger, D. (2003). Boomers, gen-xers and millennials: Understanding the new students. EDUCAUSE Review, 38(4), July/August, 37-47.

Pajares, F. (2006). Overview of social cognitive theory and of self-efficacy. Retrieved from http://www.des.emory.edu/mfp/eff.html

Prensky, M. (2001). Digital natives, digital immigrants. NCB University Press, 9(5), 1-6.

Roberts, T. G. (2006). A philosophical examination of experiential learning theory for agricultural educators. Journal of Agricultural Education, 47(1), 17-29. doi: 10.5032/jae.2006.01017

Roberts, T. G., Harlin, J. F., & Briers, G. E. (2008). Peer modeling and teaching efficacy: The influence of two student teachers at the same time. Journal of Agricultural Education, 49(2), 13-26. doi: 10.5032/jae.2008.02013

Roberts, T. G., Harlin, J. F., & Ricketts, J. C. (2006). A longitudinal examination of teaching efficacy of agricultural science student teachers. Journal of Agricultural Education, 47(2), 81-92. doi: 10.5032/jae.2006.02081

Smith, S. M. (2002). Using the social cognitive model to explain vocational interest in information technology. Information Technology, Learning, and Performance, 20(1), 1-9. (Document ID: 217198171).

Stimson, R. W. (1919). Vocational agricultural education by home projects. New York, NY: MacMillan.

Tapscott, D. (1998). Growing up digital: The rise of the Net generation. New York, NY: McGraw-Hill.

Tapscott, D. (1999). Educating the Net generation. Educational Leadership, 56(5), 6-11.

Tschannen-Moran, M., Woolfolk Hoy, A., & Hoy, W. K. (1998). Teacher efficacy: Its meaning and measure. Review of Educational Research, 68(2), 202-248. (Document ID: 33612747).

Whittington, M. S., McConnell, E., & Knobloch, N. A. (2006). Teacher efficacy of novice teachers in agricultural education in Ohio at the end of the school year. Journal of Agricultural Education, 47(4), 26-38. doi: 10.5032/jae.2006.04026

J. C. Bunch, Graduate Student

J. Shane Robinson, Associate Professor

M. Craig Edwards, Professor

Oklahoma State University

J. C. BUNCH is a Graduate Student of Agricultural Education in the Department of Agricultural Education, Communications and Leadership at Oklahoma State University, 458 Agricultural Hall, Stillwater, OK 74078, bunchj@okstate.edu

J. SHANE ROBINSON is an Associate Professor of Agricultural Education in the Department of Agricultural Education, Communications and Leadership at Oklahoma State University, 457 Agricultural Hall, Stillwater, OK 74078, shane.robinson@okstate.edu

M. CRAIG EDWARDS is a Professor of Agricultural Education in the Department of Agricultural Education, Communications and Leadership at Oklahoma State University, 456 Agricultural Hall, Stillwater, OK 74078, craig.edwards@okstate.edu
Table 1
Comparison of Early and Late Respondents
Regarding Oklahoma Agricultural Education Teachers'
Levels of Self-Efficacy, Outcome
Expectation, and Interest

                           Early        Late
                       Respondents   Respondents

Construct               M     SD       M     SD    p-value

Self-Efficacy          3.85   .65    3.68   .87     .32
Outcome Expectation    3.79   .70    3.68   .73     .49
Interest               3.81   .60    3.66   .76     .33

Note. The real limits of the scale were 1.00 to 1.49 =
strongly disagree, 1.50 to 2.49 = disagree, 2.50 to
3.49 = neutral, 3.50 to 4.49 = agree,
and 4.50 to 5.00 = strongly agree.

Table 2
Selected Characteristics of Oklahoma
Agricultural Education Teachers (n = 81)

Variable                                              f     %

Age               21 to 25 years                      5    6.2
                  26 to 30 years                      18   22.2
                  31 to 35 years                      12   14.8
                  36 to 40 years                      11   13.6
                  41 to 45 years                      7    8.6
                  46 to 50 years                      11   13.6
                  51 or older                         14   17.3
                  No Response                         3    3.7

Gender            Male                                73   90.1
                  Female                              5    6.2
                  No Response                         3    3.7

Highest level     Bachelor's                          57   70.4
  of educational  Master's                            20   24.7
  attainment      Education Specialist                1    1.2
                  Doctorate                           1    1.2
                  No Response                         2    2.5

Years of          0 to 5 years                        21   25.9
  teaching        6 to 10 years                       14   17.3
  experience      11 to 15 years                      16   19.8
                  16 to 20 years                      4    4.9
                  21 to 25 years                      6    7.4
                  26 to 30 years                      12   14.8
                  31 or more years                    4    4.9
                  No Response                         4    4.9
Teaching          Traditional                         74   91.4
  certification   Alternative                         5    6.2
  type            No Response                         2    2.5

School size       Class C = < 86 students             4    4.9
                  Class B = 86 to149 students         17   21.0
                  Class 1A = 150 to 199 students      18   22.2
                  Class 2A = 200 to 320 students      16   19.8
                  Class 3A = 321 to 482 students      7    8.6
                  Class 4A = 483 to 687 students      7    8.6
                  Class 5A = 688 to 1242 students     2    2.5
                  Class 6A = 1243 to 4461 students    8    9.9
                  No Response                         2    2.5

Access to IWBs    Yes                                 59   72.8
                  No                                  21   25.9
                  No Response                         1    1.2

Access to         Yes                                 33   40.7
  School-         Sometimes                           30   37.0
  Employed IT     No                                  10   12.3
                  No Response                         8    9.9

IWB Use           0 to 5 times per week               17   21.0
  per Week        6 to 10 times per week              19   23.5
                  11 to 15 times per week             14   17.3
                  16 to 20 times per week             10   12.3
                  21 to 25 times per week             6    7.4
                  26 to 30 times per week             1    1.2
                  30 or more times per week           2    2.5
                  No response                         12   14.8

Table 3
Oklahoma Agricultural Education Teachers'
Level of Self-Efficacy, Outcome Expectation,
and Interest Regarding the Use of IWBs (n = 81)

Item                                   M      SD

Construct 1: Self-Efficacy
  I feel confident that I can         3.93   .83
  regularly incorporate
  appropriate IWBs into
  my lessons to enhance
  student learning.
I feel confident that I can           3.90   .88
  teach relevant subject
  matter with appropriate
  use of IWBs.
I feel confident that                 3.89   .82
  I can effectively
  use IWBs in my teaching.
I feel confident that I can select    3.74   .95
  appropriate IWBs for
  instruction based
  on curriculum
  standards-based pedagogy.
I feel confident that                 3.62   .92
  I have the necessary
  skills to use IWBs for
  instruction.
I feel confident that                 3.49   .94
  I can help students when
  they have difficulty with
  IWBs.
Composite Mean                        3.76   .76

Construct 2: Outcome Expectation
  Using IWBs in the classroom         4.17   .83
  will increase my effectiveness
  as a teacher.
Using IWBs in the classroom will      4.11   1.00
  make my teaching more exciting.
Using IWBs in the classroom will      4.02   .88
  increase my productivity.
Using IWBs in the classroom will      3.99   .92
  make it easier for me to teach.
Using IWBs in the classroom will      3.93   .83
  make my teaching more satisfying.
Effectively using IWBs in the         3.60   .90
  classroom will increase my
  sense of accomplishment.
Effectively using IWBs in the         3.30   .99
  classroom will increase
  my colleagues' respect
  of my teaching ability.
My colleagues will see me as          3.25   1.00
  competent if I effectively
  use IWBs in the
  classroom.
Effectively using IWBs in the         3.23   .94
  classroom will increase
  my status among
  my colleagues.
Composite Mean                        3.73   .72

Construct 3: Interest
I am interested in learning           4.11   .76
  about new
  educational software.
I am interested in working            4.07   .70
  with IWB tools.
I have an interest in                 3.88   .87
  attending IWB workshops
  during my teaching career.
I have an interest in listening       3.74   .95
  to a famous instructional
  technologist speaking about
  effective use of IWBs.
I have an interest in working         3.47   .88
  on a project involving
  IWB concepts.
I have an interest in reading         3.16   .94
  articles or books about IWBs.
Composite Mean                        3.74   .68

Table 4
Relationships * between Oklahoma Teachers'
Self-Efficacy, Outcome Expectation, and Interest
Regarding Use of IWBs (n = 81)

Construct             Outcome Expectation   Interest

Self-efficacy                .54 *           .26 *
Outcome Expectation                          .61 *

Note. (a) Pearson-product moment
correlation coefficient; * p < .05

Table 5
Relationships (a) between Oklahoma Teachers'
Self-Efficacy, Outcome Expectation, Interest and Their Age,
Years of Teaching Experience, and Size of School (n = 81)

Construct              Age     Year of Teaching     Size
                                  Experience      of School

Self-Efficacy         -.29 *        -.26 *          -.11
Outcome Expectation   -.29 *        -.24 *          -.09
Interest               -.09          -.11           -.13

Note. (a) Spearman rho correlation coefficient; * p < .05

Table 6
Relationships (a) between Oklahoma Teachers'
Self-Efficacy, Outcome Expectation, Interest with Their
Access to IWBs, Access to School-Employed IT
Personnel, and Frequency of IWB Use per Week (n = 81)

                       Access to    Access to     IWB Use per
Construct                IWBs      IT Personnel      Week

Self-Efficacy            .32 *        .46 *          .42 *
Outcome Expectation       .16         .25 *          .23 *
Interest                 -.06          -.02           .15

Note. (a) Spearman rho Correlation Coefficient; * p < .05
COPYRIGHT 2012 American Association for Agricultural Education
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2012 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Bunch, J.C.; Robinson, J. Shane; Edwards, M. Craig
Publication:Journal of Agricultural Education
Date:Jan 1, 2012
Words:6345
Previous Article:Scientific basis vs. contextualized teaching and learning: the effect on the achievement of postsecondary students.
Next Article:Resilient agricultural educators: taking stress to the next level.
Topics:

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters