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Running Head: TRENDS IN EVALUATION VOCABULARY 1

TRENDS IN EVALUATION VOCABULARY 10

Trends in Evaluation Vocabulary

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Shakman, K., & Rodriguez, S. M. (2015). Logic models for program design, implementation, and evaluation: Workshop toolkit (REL 2015-057). Retrieved from http://eis.ed.gov/ncee/edlabs/projects/project.asp?ProjectID=401

Shakman et al. introduce a logic model toolkit that evaluators and researchers often use to help them with the various elements and instructions in designing their model. Theory approach, Activities approach, and Outcomes approach are three categories of logic models listed by the authors. The authors also go into all of the logic models and concepts, such as goals, tasks, strategy outcomes, and outcome effects. Previous analysis by Rogers et al. used similar terms, but the reasoning model was referred to as Impact Evaluation. Despite this, all are looking for the same outcomes.

Burrows, T. L., Lucas, H., Morgan, P. J., Bray, J., & Collins, C. E. (2015). Impact evaluation of an after-school cooking skills program in a disadvantaged community: back to basics. Canadian Journal of Dietetic Practice and Research, 76(3), 126-132. Retrieved from https://dcjournal.ca/doi/abs/10.3148/cjdpr-2015-005

Burrows et al. wanted to see how the Back to Basics cooking club affected eating habits in a group of people who were at high risk of obesity (2015). To test the result results, the investigators used the presentation of a reasoning model to equate Phase 1 and Phase 2 of the program. The authors identify ten main structures to characterize events or inputs in the comparison model, which offers information for the results in each Step. Though some some of the verbs used by Burrows et al. differ from those used by other sources, their vocabulary suits their intention of work. The terms used were “environment, situation, behavioral capabilities, outcomes expectations and expectancies, self-control, observational learning reinforcement, self-efficacy, emotional coping responses, and reciprocal determinism” (Burrows et al., 2015).

Zimmerman, M. A., Eisman, A. B., Reischl, T. M., Morrel-Samuels, S., Stoddard, S., Miller, A. L., Rupp, L. (2018). Youth Empowerment Solutions: Evaluation of an After-School Program to Engage Middle School Students in Community Change. Health Education & Behavior, 45(1), 20–31. Retrieved from https://journals.sagepub.com/doi/abs/10.1177/1090198117710491

Zimmerman et al. use some different vocabulary, but their wording is close to that of the previous two examples. The Empowerment Principle, for example, the words used discusses and used to assess youth services that rely on offering positive contexts to develop youth assets and involve them in community activities (Zimmerman et al., 2018). However unlike previous references, Zimmerman et al. also mentions that empowerment effects have three interconnected components: interpersonal, interpersonal, and behavioral. Furthermore, certain empowerment projects are tested using experimental or quasi-experimental designs, according to the article.

Holden L, Berger W, Zingarelli R, Siegel E.(2015). After-School Program for urban youth: Evaluation of a health careers course in New York City high schools. Information Services & Use. 35(1/2), 141-160. Retrieved from https://content.iospress.com/articles/information-services-and-use/isu773

In 2014, a study was undertaken in New York City to assess the MIM After-School Program, whose aim is to offer intellectual stimulation for marginalized children. In their analysis, the authors use similar measurement terms, such as Formal Assessment, Quantitative, and Qualitative Methods. Holden et al. (2015) continue to use terms from previous research, such as structure, presentation, and efficacy, in their assessment. While the authors' wording varies from that of other studies, the meanings do not clash with other terminologies.

Riggs, N. R., & Greenberg, M. T. (2004). After-school youth development programs: A developmental-ecological model of current research. Clinical Child and Family Psychology Review, 7(3), 177–190. Retrieved from https://link.springer.com/article/10.1023/B:CCFP.0000045126.83678.75

This article introduces some new terms while being consistent with past sources. A quasi-experimental program and randomized sample study, for example, are discussed, whereas program assessment and research are listed in relation to previous studies. While quasi-experimental designs have drawbacks, they are unable to monitor variations resulting from the selection process (Riggs & Greenberg, 2004). Although the evaluation is not specified, the glossary terms are sufficient for the analysis, and the role of the evaluators using the proposed methods was stressed (Riggs & Greenberg, 2004). Meta-analysis is often used to investigate the function of study design and intervention outcomes (Riggs & Greenberg, 2004).

Rogers, P.J & BetterEvaluation (2012). Introduction to impact evaluation. Melbourne, Australia: RMIT University and Better Evaluation. Retrieved from https://www.interaction.org/wp-content/uploads/2019/03/1-Introduction-to-Impact-Evaluation.pdf

Although Rogers et al. offer a glossary of assessment terminology, the emphasis of this paper is on Impact Evaluation. Impact evaluation is described as an investigation into initiatives, strategies, and small or large projects aimed at improving a society, with a focus on a small number of main evaluation questions that can be answered by interview or community survey (Rogers, & Better Evaluation, 2012). This method of assessment necessitates reliable data in order to establish or validate an intervention's hypothesis, quantify or explain its effects, and yield beneficial outcomes while mitigating negative consequences (Rogers et al., 2012). According to Rogers et al., defining stakeholders using Outcome Mapping, which articulates what needs to be achieved and how the action will affect the partners, is one approach that is critical for a positive effect (2012). The value of knowing what services are accessible, how they function, and what effect they have on the community is stressed (Rogers et al., 2012).

Cryan, M., & Martinek, T. (2017). Youth Sports Development Through Soccer: An Evaluation of an After-School Program Using the TPSR Model. Physical Educator, 74(1), 127–149. Retrieved from https://search.proquest.com/openview/a8136c880c3a1ec324d2c8d7aa510e5b/1?pq-origsite=gscholar&cbl=35035

Using the Teaching Personal and Social Responsibility (TPSR) model, this source assesses an after-school soccer program for boys aged 11 and 12. Cryan and Marinek (2017) research uses terms such as formative and summative tests. The used terms measure the performance of the TPSR model and the participants' behavior.

Cohen, M. A., & Piquero, A. R. (2010). An Outcome Evaluation of the YouthBuild USA Offender Project. Youth Violence and Juvenile Justice, 8(4), 373– 385. Retrieved from https://journals.sagepub.com/doi/abs/10.1177/1541204009349400

Cohen and Piquero (2010) provide an impact assessment of the YB Offender Project, as well as a perspective on the YB's criminal activity reduction efforts. They use words such as result assessment, theoretical or observational research to target a group of juvenile criminals aged 16 to 24. (Cohen & Piquero, 2010). Despite the fact that the paper mentions a tentative result assessment and program results, as well as a number of other materials, the authors do not define evaluation. However, it does have short- and long-term effects, deeming the test a success with promising findings, and proposing a more systematic and experimental analysis of the software in the future (Cohen & Piquero, 2010).

O’Hare L, Biggart A, Kerr K, Connolly P. A (2015). Randomized Controlled Trial Evaluation of an After-School Prosocial Behavior Program in an Area of Socioeconomic Disadvantage. Elementary School Journal. 116(1), 1-29. Retrieved from https://www.journals.uchicago.edu/doi/abs/10.1086/683102

O’Hare et al. (2015) used a randomized controlled trial to evaluate the effects of prosocial behavior for an after-school program known as Mate-Tricks for ages 9 through 10 designed to improve personal development and social outcomes. Although the importance of program evaluation was pointed out through the study, the effectiveness of the program until a 3-year rolling cohort design (RCT) was utilized (O’Hare et al., 2015). Furthermore, the authors use evaluation terminology that is not used with previous resources but is not conflicting with other studies including Interim outcomes and Process Evaluation with hopes to gain further insight into the program’s success.

Khoury-Kassabri, M., Sharvet, R., Braver, E., & Livneh, C. (2010). An evaluation of a group treatment program with youth referred to the juvenile probation service because of violent crime. Research on Social Work Practice, 20(4), 403–409. Retrieved from https://journals.sagepub.com/doi/abs/10.1177/1049731509338935

The research emphasizes the importance of service assessment and discusses the effects of a young offender diversion program. The intervention model was based on the Ecological model developed by Edleson and Tomlan (1992) for men assaulting their wives, as well as the cognitive-behavioral approach aimed at overt and implicit adolescent behavior (Khoury-Kassabri et al., 2010). By structuring a closed-ended membership strategy comparing short-term groups and long-term initiative success, similar language is used to define results or inputs. However, the authors do not have a comprehensive description of assessment or analysis, often using language that is consistent with their work and other tools (Khoury-Kassabri et al., 2010).

Huang, D., Silver, D., Cheung, M., Duong, N., Gualpa, A., Hodson, C., National Center for Research on Evaluation, S. and S. T. (2011). Independent Statewide Evaluation of After School Programs: ASES and 21st CCLC Year 2 Annual Report. CRESST Report 789. National Center for Research on Evaluation, Standards, and Student Testing (CRESST). Retrieved from https://files.eric.ed.gov/fulltext/ED520524.pdf

This resource provides a Theoretical Evaluation Model for assessing the efficacy and efficiency of the After-School Education and Safety (ASES) program. The role of stakeholders in providing instructional support and protection for students who are unsupervised after school hours is mentioned by the author (Huang et al., 2011). Following a thorough analysis of the literature, the authors presented a theoretical model emphasizing the value of continuing to run active research programs. The thesis differs from previous research in that it determines the organization's performance, setting, and instruction while emphasizing the importance of reliable and structured approaches for the program's success (Huang et al., 2011). Although the vocabulary differs from other descriptions, it is consistent with the writers' work and does not overlap with terms used elsewhere.

Chechak, D. J., Dunlop, J. M., & Holosko, M. J. (2019). Evaluating youth drop-in programs: The utility of process evaluation methods. Canadian Journal of Program Evaluation, 34(1). Retrieved from http://cjc-rcc.ucalgary.ca/index.php/cjpe/article/view/42976

This post includes modern words as well as jargon that is close to that used in the previous article. Method assessment, for example, is used with other outlets, but utilization-focused evaluation and transformative testing models are new. The process of assisting stakeholders in selecting the best model, approaches, theory, and material for their situation was described as utilization-focused evaluation (Chechak et al., 2019). The transformative research approach is characterized as the use of a cyclical model in which all members of the group are engaged in the research process from beginning to end (Chechak et al., 2019). Despite the fact that the source does not clarify effect assessment or other words that other articles use, this article describes utilization-focused evaluation and the transformative paradigm of study, which is an important approach to promoting the youth center's initial self-evaluation capability (Chechak et al., 2019).

Jenner, E., & Jenner, L. W. (2007). Results from the first-year evaluation of academic impacts of an after-school program for at-risk students. Journal of Education for Students Placed at Risk, 12(2), 213–237. Retrieved from https://www.tandfonline.com/doi/abs/10.1080/10824660701261144

Jenner & Jenner's (2007) study is close to the previous one in that it used a quasi-experimental approach to assess the academic impacts and outcomes of Louisiana's 21st Century Learning Centers (CCLC). The essay mentions lawmakers and the population as partners, outlining the program's effects and reflecting on intermediate and urgent consequences. However, the source does not offer a precise quote for program assessment, research, or effect evaluation context, nor does it provide a clear view of the moderate, imminent, or long-term results, but rather uses sets of impact and outcome metrics to gauge program effectiveness (Jenner & Jenner, 2007).

Wu, H., Shen, J., Jones, J., Gao, X., Zheng, Y., & Krenn, H. Y. (2019). Using a logic model and visualization to conduct portfolio evaluation. Evaluation and Program Planning, 74, 69– 75. Retrieved from https://www.sciencedirect.com/science/article/abs/pii/S0149718918302775

This source defines portfolio evaluation as the assessment of several projects with common goals that are used in accordance with a logic model. The logic model, as defined by the developers, is a graphical representation of theories and conclusions that can be used to assist with project planning, execution, and assessment (Wu et al., 2019). In addition to the normal assessment styles, such as logic models, the authors conclude that portfolio evaluations are an excellent method for communication, despite the fact that the literature on using data visualization to share evaluation results is small (Wu et al., 2019). Furthermore, the authors incorporate logic model components such as strategies, sub-strategies, events, results, and impacts into their portfolio assessment. Also listed in the source were the terms theory-based approach, outcome-based approach, and activity-based approach.

Julian, D. A., Jones, A., & Deyo, D. (1995). Open systems evaluation and the logic model: Program planning and evaluation tools. Evaluation and Program Planning, 18(4), 333– 341. https://doi/10.1016/0149-7189(95)00034-8

Julian et al. (1995) describe the logic model as a method and a basic assessment methodology used by planners and program evaluators known as the Open Systems model. The source supports the open systems assessment process by using terms with definitions for and variable, such as the problem statement, current circumstances, short term and long term outcomes (Julian et al., 1995). The vocabulary and meanings were considered to be similar to those of Shakman, K., and Rodriguez, S. M. (2015), as well as Rogers et al (2012).

References

Cohen, M. A., & Piquero, A. R. (2010). An Outcome Evaluation of the YouthBuild USA Offender Project. Youth Violence and Juvenile Justice, 8(4), 373– 385.doi/10.1177/1541204009349400

Cryan, M., & Martinek, T. (2017). Youth Sports Development Through Soccer: An Evaluation of an After-School Program Using the TPSR Model. Physical Educator, 74(1), 127–149.

Khoury-Kassabri, M., Sharvet, R., Braver, E., & Livneh, C. (2010). An evaluation of a group treatment program with youth referred to the juvenile probation service because of violent crime. Research on Social Work Practice, 20(4), 403–409. doi/10.1177/1049731509338935

O’Hare L, Biggart A, Kerr K, Connolly P. A (2015). Randomized Controlled Trial Evaluation of an After-School Prosocial Behavior Program in an Area of Socioeconomic Disadvantage. Elementary School Journal. 116(1), 1-29. doi:10.1086/683102.

Riggs, N. R., & Greenberg, M. T. (2004). After-school youth development programs: A developmental-ecological model of current research. Clinical Child and Family Psychology Review, 7(3), 177–190. doi/10.1023/B: CCFP.0000045126.83678.75

Rogers, P.J & BetterEvaluation (2012). Introduction to impact evaluation. Melbourne, Australia: RMIT University and BetterEvaluation.

Wu, H., Shen, J., Jones, J., Gao, X., Zheng, Y., & Krenn, H. Y. (2019). Using a logic model and visualization to conduct portfolio evaluation. Evaluation and Program Planning, 74, 69– 75.doi /10.1016/j.evalprogplan.2019.02.011