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Lesson plan analysis protocol (LPAP): A useful tool for researchers and educational evaluators.

ABSTRACT: In improving learning outcomes in education, we found a gap in available standard protocols to analyze pedagogical documents such as lesson plans. This study is a product of validated and reliable Lesson Plan Analysis Protocol (LPAP) supporting education stakeholders to get insight into the lesson plans (LPs) used in schools. The LPAP was found to be a valid and reliable tool that education evaluators can use to strengthen effective teaching in all grades of education. The protocol can also serve as teacher self-evaluation before lesson delivery. After validating it, we collected lesson plans to testing its usability and a qualitative survey for its inclusivity. We analyzed 36 among many collected lesson plans in two stages. We showed how to analyze averages for each of 27 LPAP items and how to analyze the mean scores for each lesson plan. We again collected reflection information from six researchers and found them appreciating the tool. Thus, LPAP is a useful tool to analyze taught or untaught lesson plans from any country and with any lesson plan format as it reserved some flexibilities to be modified to fit the context.

SUBMITTER: Ndihokubwayo K

PROVIDER: S-EPMC8760448 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Lesson plan analysis protocol (LPAP): A useful tool for researchers and educational evaluators.

Ndihokubwayo Kizito K Byukusenge Céline C Byusa Edwin E Habiyaremye Hashituky Telesphore HT Mbonyiryivuze Agnes A Mukagihana Josiane J

Heliyon 20220107 1

In improving learning outcomes in education, we found a gap in available standard protocols to analyze pedagogical documents such as lesson plans. This study is a product of validated and reliable Lesson Plan Analysis Protocol (LPAP) supporting education stakeholders to get insight into the lesson plans (LPs) used in schools. The LPAP was found to be a valid and reliable tool that education evaluators can use to strengthen effective teaching in all grades of education. The protocol can also serv ...[more]

PMID: 35059522

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Project description:BackgroundSince the start of the COVID-19 pandemic, efforts have been made to develop early warning risk scores to help clinicians decide which patient is likely to deteriorate and require hospitalization. The RECAP (Remote COVID-19 Assessment in Primary Care) study investigates the predictive risk of hospitalization, deterioration, and death of patients with confirmed COVID-19, based on a set of parameters chosen through a Delphi process performed by clinicians. We aim to use rich data collected remotely through the use of electronic data templates integrated in the electronic health systems of several general practices across the United Kingdom to construct accurate predictive models. The models will be based on preexisting conditions and monitoring data of a patient's clinical parameters (eg, blood oxygen saturation) to make reliable predictions as to the patient's risk of hospital admission, deterioration, and death.ObjectiveThis statistical analysis plan outlines the statistical methods to build the prediction model to be used in the prioritization of patients in the primary care setting. The statistical analysis plan for the RECAP study includes the development and validation of the RECAP-V1 prediction model as a primary outcome. This prediction model will be adapted as a three-category risk score split into red (high risk), amber (medium risk), and green (low risk) for any patient with suspected COVID-19. The model will predict the risk of deterioration and hospitalization.MethodsAfter the data have been collected, we will assess the degree of missingness and use a combination of traditional data imputation using multiple imputation by chained equations, as well as more novel machine-learning approaches to impute the missing data for the final analysis. For predictive model development, we will use multiple logistic regression analyses to construct the model. We aim to recruit a minimum of 1317 patients for model development and validation. We will then externally validate the model on an independent dataset of 1400 patients. The model will also be applied for multiple different datasets to assess both its performance in different patient groups and its applicability for different methods of data collection.ResultsAs of May 10, 2021, we have recruited 3732 patients. A further 2088 patients have been recruited through the National Health Service Clinical Assessment Service, and approximately 5000 patients have been recruited through the DoctalyHealth platform.ConclusionsThe methodology for the development of the RECAP-V1 prediction model as well as the risk score will provide clinicians with a statistically robust tool to help prioritize COVID-19 patients.Trial registrationClinicalTrials.gov NCT04435041; https://clinicaltrials.gov/ct2/show/NCT04435041.International registered report identifier (irrid)DERR1-10.2196/30083.

Project description:BackgroundInadequate sustainability of implementation of evidence-based interventions has led to calls for research on how sustainability can be optimized. To advance our understanding of intervention sustainability, we explored how implementation researchers conceptualized and planned for the sustainability of their implemented interventions with studies funded by the United States (US) National Institutes of Health (NIH).MethodsWe used sequential, mixed methods to explore how researchers conceptualized and planned for the sustainability of the health interventions using (1) a document review of all active and completed US NIH R01 Grants and Equivalents reviewed within the Dissemination and Implementation Research in Health (DIRH) Study Section between 2004 and 2016 and (2) a qualitative content analysis of semi-structured interviews with NIH R01 DIRH grant recipients.ResultsWe found 277 R01 profiles within the DIRH study section listed on the US NIH RePORTER website including 84 that were eligible for screening. Of the 84 unique projects, 76 (90.5%) had primary implementation outcomes. Of the 76 implementation project profiles, 51 (67.1%) made references to sustainability and none referred to sustainability planning. In both profiles and interviews, researchers conceptualized sustainability primarily as the continued delivery of interventions, programs, or implementation strategies. Few researchers referenced frameworks with sustainability constructs and offered limited information on how they operationalized frameworks. Researchers described broad categories of approaches and strategies to promote sustainability and key factors that may influence researchers to plan for sustainability, such as personal beliefs, self-efficacy, perception of their role, and the challenges of the grant funding system.ConclusionsWe explored how US NIH R01 DIRH grant recipients conceptualized and planned for the sustainability of their interventions. Our results identified the need to test, consolidate, and provide guidance on how to operationalize sustainability frameworks, and to develop strategies on how funders and researchers can advance sustainability research.

Dataset Information

Lesson plan analysis protocol (LPAP): A useful tool for researchers and educational evaluators.

Publications

Lesson plan analysis protocol (LPAP): A useful tool for researchers and educational evaluators.

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