Researchers might have difficulty deciding on appropriate statistical techniques for their research, even if they have taken many courses (Pallant, 2010). They commonly seek solutions from (1) textbooks, academic articles or similar written technical documents, (2) peers and academic advisors, and (3) internet-based resources, including social media and AI-based chatbots (Su & Yang, 2023; Güngör & Demir, 2024a, 2024b). However, limited statistical proficiency can lead to poor or wrong technique selection and biased results (Cramer, 2003; Dowdy et al., 2004). Although there are many potential guides that can be considered in finding the appropriate statistical technique, making effective use of them often depends on the competence of researcher. Without sufficient proficiency in statistics and methodology, these solutions might be ineffective (Hair et al., 2014; Coolican, 2024). While AI tools may help, they can still produce biased outcomes (Pan & Gu, 2023; Demir, 2024). Using inappropriate techniques also raises ethical concerns in research (Resnik, 2000). It is obvious that deciding on the appropriate statistical technique in research is crucial but not easy for most researchers. They may need support and guidance, at least at the starting point of their research.

There are many statistical techniques classified by data and variable characteristics (Rosner, 2016; Field, 2019; Hair et al., 2014) or research objectives and purpose of data analysis (Tabachnick & Fidell, 2019; Mertler et al., 2019). Although these classifications provide valuable insights and support, they often include a limited number of techniques. It is challenging to compile all techniques into a manually structured flowchart or decision tree. Furthermore, these classifications and frameworks may not align well with every research design or structure (Şengül&Demir, 2024). As a result, relying on such classifications can sometimes be restrictive or imprecise.

In practice, researchers may need guidance to identify appropriate techniques, allowing them to focus on learning and applying them effectively. Most of the time, they simply need simple guidance or recommendations on potential and appropriate techniques. Once researchers receive such recommendations, they can focus on the details and take steps to learn and apply the technique at their own pace.

This need served as the primary motivation for developing the ‘Statistical Technique Advisor (STA)’ as an interactive and web-based application designed to assist researchers in finding appropriate statistical techniques. STA features a unique software architecture that incorporates over 200 statistical techniques, organized into 10 modules, each accompanied by a dedicated flowchart. The development of STA was conducted under a project supported by TÜBİTAK (Project No.223K382), The Scientific and Technological Research Council of Türkiye. Through a series of nested and stepwise studies, STA was successfully developed and made available online at the following web address: https://erguldemir.shinyapps.io/StatisticalTechniqueAdvisor/

The primary purpose of this workshop is to engage participants in collaborative discussions about the challenges researchers face when identifying and deciding appropriate statistical techniques, as well as to explore and evaluate potential solutions to these challenges. Additionally, the workshop aims to provide participants with hands-on experience and insight into how such a tool, ‘Statistical Technique Advisor (STA)’, can help streamline the process of selecting appropriate statistical methods, ultimately improving the quality of their research.

This workshop aligns with Network 9, “Assessment, Evaluation, Testing, and Measurement,” particularly under the topic “Evaluation of Educational Research.” The focus is on assisting researchers, especially those with limited statistical experience, improve their ability to find appropriate statistical techniques. By introducing the ‘Statistical Technique Advisor’ and offering hands-on practice, the workshop highlights the importance of sound methodologies in evaluating educational research. This approach aims to enhance participants’ ability to make informed decisions about statistical techniques, thereby contributing to more robust and reliable educational research practices.

Target Audience This workshop is open to all researchers who feel they need support in finding appropriate statistical techniques in their research. Specifically, it is designed for researchers with low to moderate statistical and methodological backgrounds, or those at the early stages of their research careers. Process The workshop will be conducted over ninety minutes, divided into two sections. 1) First Section: Theoretical Preparations through Participatory Discussions The first section, lasting forty-five minutes, will provide a theoretical background on the challenges researchers face when deciding appropriate statistical techniques. This section will include two collaborative discussions. The first discussion will address the difficulties and challenges researchers experience in identifying appropriate statistical methods, and the second will focus on potential solutions to these challenges. At the end of this section, ‘Statistical Technique Advisor’ will be introduced with its features and its development process will be explained. 2) Second Section: Hands-On Activities The second section, also forty-five minutes, will be a practical activity where participants apply the theoretical knowledge from the first section. They will receive a task sheet containing five to ten research problems commonly encountered by researchers. Participants will first predict the appropriate statistical technique for each problem. Afterward, they will use the ‘Statistical Technique Advisor’ to refine their responses. This hands-on activity will allow participants to practice finding appropriate statistical techniques in common research designs. Data Collection Tools Three data collection tools will be employed in this workshop. 1. Information Form: First, an online information form will be sent to participants prior to the workshop, gathering information about their experiences in finding appropriate statistical techniques, the challenges they’ve encountered, and the solutions they have used. 2. Application and Workshop Evaluation Form: After the workshop, participants will be sent an online evaluation form to evaluate the 'Statistical Technique Advisor’ application and share their experiences of the workshop. 3. Task Sheet: Additionally, in the second stage of the workshop, a task sheet containing 5-10 specific tasks for common research designs will be distributed to participants. After the workshop, their initial and revised responses to the task sheet will be evaluated and personalized feedback will be provided to each participant via email.

This workshop aims to provide valuable insights and practical guidance for researchers who struggle with selecting appropriate statistical techniques in their research. By offering both theoretical background and hands-on practice, participants will gain a deeper understanding of the challenges involved in statistical decision-making and the tools available to overcome these obstacles. The participatory discussions in the first section will allow participants to share their experiences and solutions, fostering a supportive learning environment. The introduction of the ‘Statistical Technique Advisor’ application will further empower participants by providing them with an innovative tool to streamline the process of choosing the most appropriate statistical techniques for their data analysis. The second section, focused on the practical application, will help participants sharpen their skills in predicting and revising appropriate statistical techniques. By comparing their initial predictions with the app’s suggestions, participants will gain greater confidence in their ability to decide appropriate statistical techniques that align with the unique demands of their research. This hands-on experience is expected to significantly improve participants’ proficiency and reduce the challenges they face when deciding on statistical methods. Expected results include increased confidence among participants in their ability to identify suitable statistical techniques and a better understanding of the resources available for addressing common statistical challenges. The feedback provided through the data collection tools will also offer valuable insights into the effectiveness of the workshop and the application. Based on this feedback, further improvements can be made to enhance both the workshop content and the functionality of the ‘Statistical Technique Advisor’. Ultimately, this workshop will not only empower researchers with the knowledge and tools to tackle statistical challenges but will also promote a culture of collaboration and shared learning among researchers.

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