Process Evaluation Model Research Articles

The Effect of Leadership Capability and Collective Commitment With Personal Value Mediation on Cooperative Performance in Lamongan District

Purpose: This study aimed to examine the effect of Leadership Capability on cooperative performance, test the impact of Collective Commitment on harmonious performance, test the effect of Leadership Capability on unified performance by mediating personal values, and test the result of Collective Commitment on cooperative performance with moderating personal values. This study learns about leadership capabilities, collective commitment, and personal values on joint performance. Design/Methodology/Approach: The instrument test results with the validity test showed the data was declared valid. The reliability test results show that the sign of construct reliability meets, meaning that each indicator has consistency in measuring the latent variable. This research methodology is a descriptive quantitative research using descriptive analysis and inferential analysis with IBM Amos SEM (Structural Equation Modeling) analysis. Findings: The results of the data analysis show that all indicators are declared valid, and the model evaluation process can be continued. The effects of CFA CL, CC, and PV still have Mark loading factors that have not been met, so the indicators are dropped and re-estimated. The results of the Second Order LC CFA show that the most significant Mark loading factor is found in the LC4 hand, which has the most considerable influence on LC, the CC2 indicator has the most critical effect on CC, the PV2 indicator has the most significant power on PV, the KK3 hand has the most significant impact on the KK. The criteria for the best value of the CL, CC, PV, and KK models have been met to continue. The construct reliability values of CL, CC, PV, and KK indicate that each indicator consistently measures latent variables. Research, Practical & Social Implications: Aspects of organizational evaluation in evaluating the performance of cooperatives are the maintenance of annual member meetings by the provisions, development of business volume, number of members, and total remaining operating results. Originality/Value: The results of the SEM evaluation with the univariate normality test showed an excellent critical skewness ratio value, and the kurtosis indicated by the univariate data was normally distributed. The results of the outlier evaluation show that Mark evennobis is farther away from the chi-square table, meaning that there is no multivariate outlier problem, and the data is feasible to use. The results of the AVE value show that the latent variable already has good convergent validity. The CMIN/DF, RMSEA, and TLI values are by the criteria, and the CFI is good. LC. The results of hypothesis testing affect KK; CC affects KK, and LC has an effect on KK with PV and CC. Mediation does not affect cooperation with PV mediation.

Adapting the learning environment of a first year interprofessional module towards collaborative-ready graduates

BackgroundThere has been a global call for a more collaborative workforce to combat the complex healthcare challenges experienced in societies. As a result, health professions education has amended their curricula to include interprofessional education as a strategy to allow students to learn from, with and about each other across disciplines during their training. It is imperative to review the learning environment of these interprofessional modules. To determine the learning environment for the acquisition of the interprofessional core competencies, there needs to be an understanding of the changes to the module, and the impact it has on student performance over a selected period. ObjectiveThis study aimed to determine how have the changes to the material dimension of the learning environment for first-year students in an IPE curriculum promoted student learning. MethodsA document analysis research design was used to extract data over a two-year period. An adaptation of the Context, Input, Process, Product and Outcomes evaluation model was to determine how changes to the learning environment of students registered for a first year interprofessional module, promoted learning. ResultsThe findings reveal that curriculum changes made to the location and setting can yield improvements in the development and enhancement of the selected interprofessional education core competencies. ConclusionThis study concludes that in alignment with the learning styles of the 21st century student, curriculum development should include an enhanced form of deeper learning in the light of the fourth industrial revolution.

Indicators for evaluation of model performance: irrigation hydraulics applications

Several mathematical models have been developed for applications in the hydraulics of irrigation systems and several performance indicators of these models are used and suggested by the literature. Thus, the objective of this work was to investigate the performance of statistical indicators for the evaluation of models in irrigation hydraulics. For this, three case studies which represent typical irrigation hydraulics modeling were used to assess the indicators. A set of indicators were analyzed: a) difference-based: mean absolute error, mean square error, root mean square error, scaled root mean square error, and percent mean absolute error; b) efficiency-based: Nash-Sutcliffe and Legates-McCabe; c) correlation coefficient ( ); d) coefficient of determination ( ); e) index of agreement index ( ); f) Camargo and Sentelhas index ( ); and g) graphical methods: regression error characteristic curve based on relative absolute error and 1:1 scatter plot. For the evaluated cases, which are physical phenomena, differentiable indicators are similar measures and it is appropriate to report either or both indices. The assessment of models must also be supported by graphical analysis, which shows the real scenario of errors in the model evaluation processes. Efficiency-based indicators, , , , and are not recommended and should be avoided in modeling of irrigation hydraulics.

Predicting suitable habitats of the major forest trees in the Saïda region (Algeria): A reliable reforestation tool

Abstract Modeling potential habitat for plant species is an appropriate approach to maintain biodiversity, developing proper reforestation campaigns, and rehabilitating ecosystems. In this study, we investigated the potential distributions of four forest species, namely, Quercus faginea Lam.; Q. ilex L.; Tetraclinis articulata (Vahl) Mast.; and Pistacia atlantica Desf. In the north-western Algeria at Saïda region. The MAXENT method was used to model the habitats of these species using topographic data as predictive variables at a resolution of 100 m. Moreover, the model evaluation process was achieved using the area under the operating characteristic curve of the receiver (AUC) and Jackknife test. The generated models were found to be accurate. AUC results are ranging between 0.98 and 0.91 for the training set and 0.87 and 0.97 for the testing set. The results of the distribution probability of this study provide a useful tool for the local decision-makers of reforestation campaigns.

Scientific Machine and Deep Learning Investigations of the Local Buckling Behaviour of Hollow Sections

AbstractThe recent advent of Machine and Deep Learning (ML/DL) increased interest among applicability of data‐driven methods to design and verification in structural civil engineering concerned, specifically with members made of steel within this paper. Scientific ML (SciML) follows the idea of combining domain knowledge with the abilities of ML and DL algorithms to make the best out of both worlds. This paper investigates the SciML algorithms Random Forrests, XGBoost and a deep neural network model for the prediction of the cross‐section dependent local buckling reduction factor χ for different hot rolled and cold‐formed SHS and RHS profiles made of mild and high strength steel. The process of data collection, cleaning, compilation and model training and evaluation is described. It is found, that especially tree‐based methods can serve as feature importance and selection methods and have similarly high predictive capabilities such as deep neural networks for the case of of the cross‐section dependent local buck‐ling reduction factor χ for different hot rolled and cold‐formed SHS and RHS profiles made of mild and high strength steel. The data of this paper furthermore serve as the initial data‐set for establishing the Github repository “SciML4StructEng_Repository”. This repository which will foster the dissemination of data sets for structural civil engineering to allow the prototyping, development and benchmark testing of scientific machine and deep learning (SciML) algorithms.

Quantifying Arctic oil spilling event risk by integrating an analytic network process and a fuzzy comprehensive evaluation model

The development of economic globalization and increasing ice melting in Arctic area enables Arctic shipping activities more convenient. Exploring impact of extreme events (i.e., oil spilling) occurring in the Arctic region attracts increasing interest from the shipping industry and maritime traffic community. For the sustainable Arctic development and marine environment protection, it is in need to develop a comprehensive risk assessment framework to suppress potential loss caused by Arctic oil spill event. To that aim, the study quantifies the Arctic oil spill event impact with an ensemble framework supported by the analytic network process (ANP) and fuzzy comprehensive evaluation model. More specifically, we quantify varied factors (e.g., environment, economy, social influence, recovery mode) and establish oil spilling risk level via the help of fuzzy comprehensive evaluation model in the proposed framework. Experimental results suggest that our proposed framework can accurately quantify influence of an oil spilling event in Arctic area, and thus the potential risk level can be accurately identified. The proposed framework provides a novel and reasonable decision-making tool, which can help Arctic related communities conduct varied activities in a more reasonable yet lower-risk manner.

Innovating workplace learning: Training methodology analysis based on content, instructional design, programmed learning, and recommendation framework.

The quality of sales processes is crucial in automotive and directly related to the firm’s competitive advantage and financial success. Sales training is the most prevalent intervention to guarantee quality and productivity. Extant literature has attempted to measure training effectiveness adequately, and the Context, Input, Process, and Product evaluation (CIPP) model has been a popular approach. This study endeavored to advance current literature and suggest a novel effectiveness framework, Content, Instructional design, Programmed learning, and Recommendation (CIP-R). The framework was applied to examine three different methodologies—traditional, pure digital, and hybrid training—collecting 583 instances from the automotive sales training conducted from 2019 to 2020 in South Korea. The findings advocate the importance of human elements, the role of efficacy, and self-determination in generating learning transferability, leading to performance in the digital age.

A standard protocol for describing the evaluation of ecological models

Numerical models of ecological systems are increasingly used to address complex environmental and resource management questions. One challenge for scientists, managers, and stakeholders is to appraise how well suited these models are to answer questions of scientific or societal relevance, that is, to perform, communicate, or access transparent evaluations of ecological models. While there have been substantial developments to support standardised descriptions of ecological models, less has been done to standardise and to report model evaluation practices. We present here a general protocol designed to guide the reporting of model evaluation. The protocol is organised in three major parts: the objective(s) of the modelling application, the ecological patterns of relevance and the evaluation methodology proper, and is termed the OPE (objectives, patterns, evaluation) protocol. We present the 25 questions of the OPE protocol which address the many aspects of the evaluation process and then apply them to six case studies based on a diversity of ecological models. In addition to standardising and increasing the transparency of the model evaluation process, we find that going through the OPE protocol helps modellers to think more deeply about the evaluation of their models. From this last point, we suggest that it would be highly beneficial for modellers to consider the OPE early in the modelling process, in addition to using it as a reporting tool and as a reviewing tool.

Formal definition of the MARS method for quantifying the unique target class discoveries of selected machine classifiers

Conventional binary classification performance metrics evaluate either general measures (accuracy, F score) or specific aspects (precision, recall) of a model's classifying ability. As such, these metrics, derived from the model's confusion matrix, provide crucial insight regarding classifier-data interactions. However, modern- day computational capabilities have allowed for the creation of increasingly complex models that share nearly identical classification performance. While traditional performance metrics remain as essential indicators of a classifier's individual capabilities, their ability to differentiate between models is limited. In this paper, we present the methodology for MARS (Method for Assessing Relative Sensitivity/ Specificity) ShineThrough and MARS Occlusion scores, two novel binary classification performance metrics, designed to quantify the distinctiveness of a classifier's predictive successes and failures, relative to alternative classifiers. Being able to quantitatively express classifier uniqueness adds a novel classifier-classifier layer to the process of model evaluation and could improve ensemble model-selection decision making. By calculating both conventional performance measures, and proposed MARS metrics for a simple classifier prediction dataset, we demonstrate that the proposed metrics' informational strengths synergize well with those of traditional metrics, delivering insight complementary to that of conventional metrics.

THE PERCEPTION OF PARENT'S ABOUT ONLINE LEARNING USING PROCESS EVALUATION MODEL IN TEJAKULA DISTRICT

Online learning has been implemented as an alternative to face-to-face learning. The learning process was carried out from home online. Learning at home causes parents to be involved in the learning process of their children. Parents' perspective is needed in knowing the implementation of online learning. This study uses descriptive qualitative research methods. The data was generated using interview instruments and questionnaires with a focus on the process evaluation model. The purpose of this article is to find out the perspective of parents on the online learning process during a pandemic situation. The sample taken is 20 parents of students who are implementing the online learning process in Tejakula sub-district. The results showed that parents were able to provide motivation to students during the learning process. However, there are some obstacles that they cannot control when contributing to learning. Keywords: Online learning, parents perception, process evaluation model

Evaluation of Teaching Practice Course According to The Opinions of Teaching Staff, Practice Teachers and Pre-Service Teachers

The aim of this study is to evaluate the teaching practice course according to the views of the teaching staff, practice teachers and physical education teacher candidates who took the teaching practice course. As the program evaluation model, Stufflebeam's Context, Input, Process and Product Evaluation Model (CIPP) was used. Mixed research method, in which quantitative and qualitative research methods are used together, was used in the research. The quantitative data collection group of the research consists of physical education teacher candidates (n:63) who took the Teaching Practice course at Hatay Mustafa Kemal University Physical Education and Sports School in the 2021-2022 academic year. The qualitative data consisted of 7 instructors and 7 practice teachers who provided consultancy to the pre-service teachers participating in the study. The data collection tools of the research are the Teaching Practice Evaluation Questionnaire and Semi-Structured Interview Form developed by Aslan and Sağlam (2017). In the study, data were collected in two stages: In the first stage, quantitative data were collected and in the second stage, semi-structured interviews were conducted to explain the quantitative data in more detail. The SPSS package program was used in the analysis of the quantitative data obtained in the study, and the mean and standard deviation values for each item were included. In the analysis of qualitative data, descriptive analysis technique was used. As a result of the study, while there were some failing points in the context, input and process dimensions, the findings obtained in the product dimension indicated that the physical education teacher candidates considered the teaching practice to be effective at a sufficient level. When the data obtained from the interviews were examined, it was observed that all three stakeholders of the course made the same or similar statements on some issues, and while it was observed that their views were compatible with each other, the statements of the stakeholders were different from each other in some items. Depending on the results, suggestions can be made such as providing the necessary conditions in the practice schools, providing the necessary materials to the teacher candidates in order for the teaching practice to be efficient, and regularly giving the two-hour seminar courses given at the school by the practice instructors.

Is the Emergency Distance Teaching ‎Experience Different in Postgraduate ‎Programs?

This study evaluates emergency remote teaching for postgraduate programs. A descriptive-analytic ‎method was used, including quantitative and qualitative tools. A questionnaire (N = 144) was ‎administered based on the context, input, process, and product (CIPP) model for evaluation, and semi-‎structured interviews (N = 6 participants) were conducted to provide a comprehensive depiction ‎incorporating participants’ views from three Saudi universities. The results revealed participants had a ‎positive bias regarding their experience; the results were similar to those of a number of studies but ‎revealed increased consistency of distance learning characteristics, specifically, data, exceptions, and ‎objectives of higher stages. This study also revealed several transitive and positive effects along with ‎challenges that seem to confront not only emergency distance teaching but the whole experience of ‎distance learning.‎

Evaluation of seawater intrusion and water quality prediction in Dagu River of North China based on fuzzy analytic hierarchy process exponential smoothing method.

It is of great significance to evaluate the seawater intrusion degree and predict the change of water quality for coastal groundwater resources. This study takes Dagu River in Jiaodong Peninsula of North China as the target area and combines the relevant theoretical research results to build a seawater intrusion fuzzy analytic hierarchy process (AHP) evaluation model. Five sensitive indicators of water quality, such as Cl-, SO42-, NO3-, TH, and TDS, were selected to evaluate the seawater intrusion level of the long series monitoring data in Xilaiwan, Guanzhuang, and Ligezhuang of Dagu River Basin by using the basic fuzzy mathematics principles and the improved hierarchical analysis method. In this study, the cubic exponential smoothing method was applied to predict groundwater quality change in Dagu River Basin. In order to evaluate the change of seawater intrusion in detail and make timely prediction, this paper innovatively divided the classification standard of seawater intrusion degree based on relevant norms and scholars' research and predicted the evaluation level of seawater intrusion by using long series historical observation data combined with fuzzy analytic hierarchy process.The cubic exponential smoothing method which has the characteristics of simple and fast was introduced to fit the observation elements, and the historical data were used to verify the prediction of the future development trend. Compared with the evaluation results of seawater intrusion by traditional methods, this study can reflect the whole development trend of seawater intrusion in detail and has the characteristics of more reasonable, accurate, and practical. It also provides a certain reference for the future seawater intrusion prevention. In addition to this case, the method proposed in this study will be applicable to a wider range of coastal zones, providing a new idea for the rational management and control of coastal groundwater resources.

Exploring low-tech opportunities for higher education mathematics lecturers in an emergency techno-response pedagogy

The education sector, among others, was severely affected by the coronavirus disease 2019 (COVID-19) pandemic. Because mathematics has always been singled out as a subject that needs more verbal communication and interaction, rapid adjustments had to be made by mathematics lecturers in higher education institutions to try and facilitate normal teaching and learning remotely through emergency open distance methods. Lecturers were forced to examine prevailing practices with a view to creating innovative and workable solutions to the emergency challenges without compromising the quality previously experienced during face-to-face classroom interactions. The article developed through a simple technology a conceptual framework for emergency remote teaching (ERT) in an emergency techno-response pedagogy (ETRP). The key was to demonstrate an innovative instructional strategy for teaching mathematics using a simple technology instead of an advanced or complicated mathematics software in the move from face-to-face to fully online teaching during a crisis. A development qualitative virtual case study was conducted that involved observing live and recorded mathematics lectures and interviewing an innovative lecturer of mathematics in the delivery of complex numbers at a graduate school in South Africa. The facilitation of the lesson through a simple and inexpensive technology (Microsoft OneNote) guided the development of a conceptual framework for ERT within an ETRP. The Context, Input, Process, and Product (CIPP) evaluation model was used as a theoretical framework to guide the analysis and conceptualisation of the lessons. Results provided guidelines through a conceptual framework for ERT that included a unique model of a lesson plan and advantages of using a simple technology in ERT instead of advanced mathematical software. The article contributes to the knowledge base in planning future ERT interventions.

Software quality: Application of a process model for quality-in-use assessment

Quality-in-use characteristics can be measured to assess the quality of the software and even point out problems in its production since they reflect the quality of the system perceived by the end-users identified in the running systems. Measuring such characteristics is a way of verifying that the software meets the requirements and expectations of the interested parties.This study presents the validation of a process model for the evaluation of the quality-in-use characteristics of a system. The model works with the identification and measurement of important characteristics of the system to determine the quality of the software, and thus identify potential problems that may inhibit its use.We applied our process model in a clinical decision support system in the oncology field using a questionnaire for gathering data for the measurement. The questionnaire mainly sought to identify user satisfaction with the use of the software, and the answers permitted us to measure the quality-in-use characteristics of the system.Our experiments revealed the adequacy of our evaluation process model and the evaluated CDSS reached a score of 71.35, which is advantageous according to our standard of measures and meets the expectations of users.

CONTEXT OF PROFESSIONAL DEVELOPMENT POLICIES AND TEACHER OF BUSINESS STUDIES COMPETENCY IN PUBLIC SECONDARY SCHOOLS IN KAJIADO COUNTY, KENYA

Potent policies directing professional development for teachers of Business studies focus on skills and competencies which address specific needs of learners for high achievement. Professional development for teachers of Business studies has been a trending phenomenon in the education sector in Kenya for enhancing effective teaching and learning. Contemporary training prepares teachers of Business studies with appropriate competencies for equipping learners with skills and capabilities to thrive in a dynamic and interconnected world that joins and engages the sense of curiosity. In addition, teachers of Business studies receive updates on modern pedagogical skills through pre-service training and capacity building and job motivation through teacher promotion for raising productivity. Professional development for teachers is guided by feasible policies which act as control mechanism for enhancing discipline, order and accountability in the teaching profession. Thus, this study determined the influence of policies guiding professional development on teacher of Business studies competency in Kajiado county, Kenya. The study was premised on the Context evaluation, Input evaluation, Process evaluation and Product evaluation model. Anchored on a descriptive survey design, the study targeted a population of 42 respondents from eleven public secondary schools and education offices in Isinya sub-county; Kajiado county. Data was gathered from teachers of Business studies using questionnaires and from school principals and sub-county education officials using interview schedules. Data collected was coded and fed into SPSS software version 25.0 and statistical analysis using inferential and descriptive statistics was done on cross-tabulations. The study found that policies guiding the professional development of teachers of Business studies were significantly related to teacher competency. The study recommends the Teachers Service Commission (TSC) to formulate more feasible policies that guide professional development of teachers of Business studies through capacity building training, targeting contemporary issues surrounding Business studies and equipping teachers with practical skills critical for enhancing socio-economic development. Further, the study recommends the TSC to formulate attainable policies that guide and create morale of teachers of Business studies through continuous job promotion for high learner achievement.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0939/a.php" alt="Hit counter" /></p>

Formal definition of the MARS method for quantifying the unique target class discoveries of selected machine classifiers

Conventional binary classification performance metrics evaluate either general measures (accuracy, F score) or specific aspects (precision, recall) of a model’s classifying ability. As such, these metrics, derived from the model’s confusion matrix, provide crucial insight regarding classifier-data interactions. However, modern- day computational capabilities have allowed for the creation of increasingly complex models that share nearly identical classification performance. While traditional performance metrics remain as essential indicators of a classifier’s individual capabilities, their ability to differentiate between models is limited. In this paper, we present the methodology for MARS (Method for Assessing Relative Sensitivity/ Specificity) ShineThrough and MARS Occlusion scores, two novel binary classification performance metrics, designed to quantify the distinctiveness of a classifier’s predictive successes and failures, relative to alternative classifiers. Being able to quantitatively express classifier uniqueness adds a novel classifier-classifier layer to the process of model evaluation and could improve ensemble model-selection decision making. By calculating both conventional performance measures, and proposed MARS metrics for a simple classifier prediction dataset, we demonstrate that the proposed metrics’ informational strengths synergize well with those of traditional metrics, delivering insight complementary to that of conventional metrics.

Policies Guiding Pedagogy and Teacher of Business Studies Competency in Kajiado County, Kenya: Instructional Skills’ Policy Discourse

Operative utilization of policies guiding instructional skills is key in shaping ways in which teachers of Business studies incorporate varied methods of teaching, assessment of learning and integration of pedagogical resources for heightening learner academic achievement. Proper formulation and implementation of feasible policies guiding instructional skills possessed by teachers of Business studies tend to ensure even accommodation of learners during instruction process regardless of differences in learning preferences. This study pored over influence of policies directing teaching methods, assessment methods and pedagogical resources employed by teachers of Business studies in Kajiado county; Kenya. The study adopted Descriptive survey design and was informed by Context Evaluation, Input Evaluation, Process Evaluation and Product Evaluation (CIPP) model. A total of 42 respondents from eleven secondary schools in Isinya sub- county were targeted during the study. Data was collected using questionnaires as the main collection tool and interview schedules. The data gathered was ciphered and fed into SPSS software version 25.0 and statistical analysis using inferential and descriptive statistics was done on cross tabulations. The findings revealed that policies on instructional skills were significantly related to teacher competency. Informed by the findings, the study recommends that the Teachers Service Commission (TSC) and Ministry of Education (MoE) should formulate more policies that emphasis on instructional skills which lead teachers of Business studies to accommodate all learners during learning process. Further, the study recommends that the MoE should make teacher training in the country more practical by formulating policies that improve teaching practice period and training institutions to frequent micro teaching sessions, embracing diverse methods of teaching, assessment and guided choice of pedagogical resources.

The Valorising Pitch: How Digital Start‐ups Leverage Intermediary Coverage

AbstractAs an unknown quantity, new ventures rely on influential intermediaries to endorse them. However, in some areas, like digital entrepreneurship, there is fierce competition for intermediary attention. Failing to garner intermediary support can mean ventures lack the resources needed to prosper. Still, it is unclear how they attract coverage, how intermediaries evaluate those vying for attention, and what influence this has on venture development. We conducted qualitative inductive research on how digital ventures sought coverage from industry analysts. Our process model of intermediary evaluation shows how ventures must perform a ‘valorising pitch’ to move from being an unknown quantity to engaging the intermediary to being valorised. Drawing on valuation studies scholarship, we propose an enhanced model of intermediary evaluation that depicts industry analysts as not just identifying but also ‘creating’ the value of ventures. We offer contributions to the literature on new venture development, intermediaries and digital entrepreneurship.

Developing an Intervention and Evaluation Model of Outdoor Therapy for Employee Burnout: Unraveling the Interplay Between Context, Processes, and Outcomes.

BackgroundBurnout is a major societal issue adversely affecting employees’ health and performance, which over time results in high sick leave costs for organizations. Traditional rehabilitation therapies show suboptimal effects on reducing burnout and the return-to-work process. Based on the health-promoting effects of nature, taking clients outdoors into nature is increasingly being used as a complementary approach to traditional therapies, and evidence of their effectiveness is growing. Theories explaining how the combination of general psychological support and outdoor-specific elements can trigger the rehabilitation process in outdoor therapy are often lacking, however, impeding its systematic research.AimThe study aims to develop an intervention and evaluation model for outdoor therapy to understand and empirically evaluate whether and how such an outdoor intervention may work for rehabilitation after burnout.Methodological ApproachWe build on the exemplary case of an outdoor intervention for rehabilitation after burnout, developed by outdoor clinical psychologists in Netherlands. We combined the generic context, process, and outcome evaluation model and the burnout recovery model as an overarching deductive frame. We then inductively specified the intervention and evaluation model of outdoor therapy, building on the following qualitative data: semi-structured interviews with outdoor clinical psychologists and former clients; a content analysis of the intervention protocol; and reflective meetings with the intervention developers and health promotion experts.ResultsWe identified six key outdoor intervention elements: (1) physical activity; (2) reconnecting body and mind; (3) nature metaphors; (4) creating relationships; (5) observing natural interactions; and (6) experiential learning. The results further showed that the implementation of these elements may facilitate the rehabilitation process after burnout in which proximal, intermediate, and distal outcomes emerge. Finally, the results suggested that this implementation process depends on the context of the therapist (e.g., number of clients per day), therapy (e.g., privacy issues), and of the clients (e.g., affinity to nature).ConclusionThe intervention and evaluation model for outdoor therapy shows how key outdoor intervention elements may contribute to the rehabilitation process after burnout. However, our model needs to be further tested among a larger group of clients to empirically evaluate whether and how outdoor therapy can support rehabilitation.