Types Of Questions Research Articles

What’s Your Problem? Writing Effective Research Questions for Quality Publications

Research questions play a central role in papers, indicating the phenomenon or problem that is being addressed, and clearly stating what is being investigated. Indeed, the presence of research questions within a research article is an established quality indicator, and research questions form the basis of determining hypotheses, methodology, methods, and how interpretations and analysis of outcomes are undertaken. Given the key purpose of a research article is to communicate the phenomenon or problem that is being addressed, research questions play a central role in clearly stating what is being investigated. The Journal of University Teaching and Learning Practice (JUTLP) seeks to publish high quality research papers which offer impactful guidance for teaching and learning practice in higher education. In this editorial, we explore what research questions are, how they are used, their key characteristics, different types of questions, and how to write them. We also make practical recommendations for authors, reviewers, and editors in how to use research questions, what to look out for when reviewing manuscripts and making decisions, and how to best support authors in producing quality publications by ensuring impactful research questions are included.

Enhancing Assessment Practices with Moodle: A Comprehensive Study on Teachers’ Use of Different Question Types and the Impact of FastTest PlugIn

This study investigates the evolution of online assessment practices through Moodle, a leading Learning Management System (LMS). It explores Moodle’s array of question types alongside the transformative impact of FastTest PlugIn (FTP) on educators’ assessment methods during and after the COVID-19 pandemic. This research examines the efficacy of various question types and import formats for large-scale question elaboration. Surveys have been conducted before and after developing courses to train educators on FTP. By analysing trends before and after adopting FTP, the study aims to gain insight into how educators from different universities and disciplines have adapted their assessment strategies among technological advancements. The introduction of FTP has significantly simplified question creation and integration within Moodle. The study also highlights differences in assessment practices between STEM and non-STEM disciplines. Surveys indicate that, following the FTP training course, the use of all question types has increased: Matching (35%), Missing Word (39%), and Cloze (22%). This work provides a comprehensive overview of current LMS trends and Moodle’s evolving role in educational technology. It emphasises the impact of technological advancements, such as FTP, on assessment practices and aims to offer actionable insights for enhancing online assessments.

Evidence-Based Potential of Generative Artificial Intelligence Large Language Models on Dental Avulsion: ChatGPT Versus Gemini.

In this study, the accuracy and comprehensiveness of the answers given to questions about dental avulsion by two artificial intelligence-based language models, ChatGPT and Gemini, were comparatively evaluated. Based on the guidelines of the International Society of Dental Traumatology, a total of 33 questions were prepared, including multiple-choice questions, binary questions, and open-ended questions as technical questions and patient questions about dental avulsion. They were directed to ChatGPT and Gemini. Responses were recorded and scored by four pediatric dentists. Statistical analyses, including ICC analysis, were performed to determine the agreement and accuracy of the responses. The significance level was set as p < 0.050. The mean score of the Gemini model was statistically significantly higher than the ChatGPT (p = 0.001). ChatGPT gave more correct answers to open-ended questions and T/F questions on dental avulsion; it showed the lowest accuracy in the MCQ section. There was no significant difference between the responses of the Gemini model to different types of questions on dental avulsion and the median scores (p = 0.088). ChatGPT and Gemini were analyzed with the Mann-Whitney U test without making a distinction between question types, and Gemini answers were found to be statistically significantly more accurate (p = 0.004). The Gemini and ChatGPT language models based on the IADT guideline for dental avulsion undoubtedly show promise. To guarantee the successful incorporation of LLMs into practice, it is imperative to conduct additional research, clinical validation, and improvements to the models.

Commercial forensic interviewing in the South African context: the Ponaletso CFI framework

Purpose The continued prevalence of financial crime and the lack of effective commercial forensic interviewing strategies prompted the development, presented here, of a conceptual framework to explain the relational dynamics conducive to interactions during a commercial forensic interview (CFI). The purpose of this study is to present such a framework which may facilitate the process of obtaining admissible evidence in different forums. Design/methodology/approach A grounded theory approach was adopted to develop a conceptual framework, drawing on the findings of a scoping review, direct observations of interactions involving commercial forensic practitioners (FPs) and interviewees, and data obtained from semi-structured interviews, making use of critical realism as a meta-theoretical framework. Findings Data obtained from the review informed the integrated approach of the conceptual framework, thus combining the structure of the PEACE model and creating an optimal interpersonal context informed by the person-centred approach (PCA). Observational data were used to identify the relational qualities associated with the interpersonal styles (clusters of relational qualities) of FPs in the CFI context, thereby contributing to complex relational dynamics. Interview data were used both to describe effective and ineffective interpersonal styles and how they played out in the CFI with interviewees, yielding information that unfortunately proved not to be admissible in a legal context. The findings of the different phases indicated the need for an integrated conceptual approach, the Ponaletso CFI framework, which draws on the structure of the PEACE model and the PCA, as expressed in the relational qualities of interactional pattern analysis (IPA). The framework consists of the interview stage (before, during and after), the structure (phases) of the PEACE model, the type of questions (open- or closed-ended) according to the PCA, FPs’ interpersonal styles (clusters of relational qualities as explained by IPA) and the observable relational dynamics between FPs and interviewees. When FPs use the Ponaletso CFI framework, there is a greater likelihood of extracting admissible evidence because the interview is guided by a clear structure with a step-by-step questioning approach by FPs, while taking into consideration the relational dynamics to which they contribute. Originality/value The proposed conceptual framework considers relational dynamics and how FPs can navigate towards optimal relational dynamics in CFI contexts. FPs can apply the structure, ask appropriate questions at the relevant phases and observe the relational dynamics playing out in the interpersonal context of the CFI. To the best of the authors’ knowledge, this is the first attempt at creating an integrated interviewing framework for conducting CFIs aligned with the legal context in South Africa. Using the Ponaletso CFI framework may aid FPs in obtaining admissible evidence and facilitate an optimal interpersonal context during commercial forensic investigations while respecting interviewees’ constitutional rights.

Mesopelagic Fish Traits: Functions and Trade‐Offs

ABSTRACTFishes inhabiting the mesopelagic zone of the world's oceans are estimated to account for the majority of the world's fish biomass. They have recently attracted new attention because they are part of the biological carbon pump and have been reconsidered as a contribution to food security. Hence, there is an urgent need to understand how environmental conditions and species interactions shape their assemblages, and how they contribute to the functioning of marine ecosystems. Trait‐based approaches are valuable for addressing these types of questions. However, the biology and ecology of mesopelagic fishes are understudied compared to fishes in shallow and epipelagic waters. Here, we synthesise existing knowledge of traits of mesopelagic fishes and relate them to their role in survival, feeding and growth and reproduction, the key functions that contribute to fitness. Vertical migrations, specialised vision and the use of bioluminescence are among the most striking adaptations to the conditions in the mesopelagic realm. Many traits are interrelated as a result of trade‐offs, which may help to understand selection pressures. While morphological traits are straightforward to observe, major knowledge gaps exist for traits that require frequent sampling, assessment under experimental conditions or age determination. The unique adaptations of mesopelagic fishes need to be included in management strategies as well as fundamental research of the habitat.

국어과 중등교사 임용시험(2002-2024) ‘고전 시가’ 영역의 분석 및 방향

Objectives The purpose of this study was to analyze the questions in the ‘classical poetry’ area in the Korean Language Department Secondary Teacher Appointment Test (2002-2024), and to suggest what direction to proceed in the future. Methods Questions in the classical poetry area were extracted from the Korean language department secondary teacher appointment test questionnaire and analyzed ‘tendency’ and ‘type of question’ based on the direction and principles of questions provided by the Korea Institute for Curriculum and Evaluation. Results The tendency of the questions could be divided into three main categories. First, there was a great tendency to consist of 2-3 passages only within the classical poem. Second, there was a bias in the classical poem section that is presented every year. Third, there were many cases where the works that were presented reappeared in different forms with similar content. The types of questions were analyzed by dividing them by period. First, in the 2000s, there was a great tendency to write questions by memorizing knowledge or content about the work. Second, questions before and after 2010 were presented focusing on knowledge of literary history and understanding and analysis of works. Third, the written questions from 2014 to the present are presented to allow objective evaluation as much as possible, and the narrative questions are presented in the direction of analysis, reasoning, synthesis, and evaluation based on data. Conclusions Based on the analysis results, four directions for the future classical poetry appointment test are proposed. First, it is necessary to expand the scope of complex passages in classical poetry. Second, reduce the deviation of the frequently asked branches, and evenly present the branches of oral literature, Korean literature, and Chinese literature. Third, develop questions to measure more diverse and higher-order thinking. Fourth, the questions are presented so that the essence of the classic poem, “a poem” and “a song (歌)” can be confirmed or realized.

Exploration Into The Ability of Fifth-Grade Students To Solve Decimal Problems Using Proportional Reasoning

Proportional Reasoning is a complex mathematical way of thinking about interconnected ideas such as multiplication and division of whole numbers, fractions, ratios, powers, measurements, and percent. This research aims to identify students' thinking processes in solving decimal problems that require proportional reasoning. This research was conducted on 5th grade elementary school students in Klaten, Central Java, Indonesia, using test instruments, interviews and documentation studies. The test given consists of five types of questions, namely tests on questions that require students to use additive, multiplicative thinking skills, use reasonable or appropriate ratios, build unit structures (groupings), and understand invariants. The research results found that the proportional reasoning indicator that was more dominantly used by students was the ability to think multiplicatively, while the sub-indicators were writing and completing calculations but the final results were not correct. Apart from that, other findings explain that the low ability is due to the prerequisite material not being mastered, students not understanding the questions, and students not understanding the concept of the topic. Thus, these results confirm that proportional reasoning abilities in grade 5 elementary school are still quite low.

Informatics assessment of COVID-19 data collection: an analysis of UK Biobank questionnaire data

BackgroundThere have been many efforts to expand existing data collection initiatives to include COVID-19 related data. One program that expanded is UK Biobank, a large-scale research and biomedical data collection resource that added several COVID-19 related data fields including questionnaires (exposures and symptoms), viral testing, and serological data. This study aimed to analyze this COVID-19 data to understand how COVID-19 data was collected and how it can be used to attribute COVID-19 and analyze differences in cohorts and time periods.MethodsA cohort of COVID-19 infected individuals was defined from the UK Biobank population using viral testing, diagnosis, and self-reported data. Changes over time, from March 2020 to October 2021, in total case counts and changes in case counts by identification source (diagnosis from EHR, measurement from viral testing and self-reported from questionnaire) were also analyzed. For the questionnaires, an analysis of the structure and dynamics of the questionnaires was done which included the amount and type of questions asked, how often and how many individuals answered the questions and what responses were given. In addition, the amount of individuals who provided responses regarding different time segments covered by the questionnaire was calculated along with how often responses changed. The analysis included changes in population level responses over time. The analyses were repeated for COVID and non-COVID individuals and compared responses.ResultsThere were 62 042 distinct participants who had COVID-19, with 49 120 identified through diagnosis, 30 553 identified through viral testing and 934 identified through self-reporting, with many identified in multiple methods. This included vast changes in overall cases and distribution of case data source over time. 6 899 of 9 952 participants completing the exposure questionnaire responded regarding every time period covered by the questionnaire including large changes in response over time. The most common change came for employment situation, which was changed by 74.78% of individuals from the first to last time of asking. On a population level, there were changes as face mask usage increased each successive time period. There were decreases in nearly every COVID-19 symptom from the first to the second questionnaire. When comparing COVID to non-COVID participants, COVID participants were more commonly keyworkers (COVID: 33.76%, non-COVID: 15.00%) and more often lived with young people attending school (61.70%, 45.32%).ConclusionTo develop a robust cohort of COVID-19 participants from the UK Biobank population, multiple types of data were needed. The differences based on time and exposures show the important of comprehensive data capture and the utility of COVID-19 related questionnaire data.

Maternal Question Use Relates to Syntactic Skills in 5- to 7-Year-Old Children.

This study examined how mothers' question-asking behavior relates to their child's syntactic skills. One important aspect of maternal question-asking behavior is the use of complex questions when speaking with children. These questions can differ based on both their purpose and structure. The purpose may be to seek out information, to teach, or to get a simple yes/no response. Questions may even be rhetorical, with no answer intended at all. Structurally, questions can include a wh-word (who, what, when, where, why, and how) or not; however, these wh-questions are important because they elicit utterances from the child and support vocabulary development. Despite wh-questions eliciting a response from children, it remains unknown how these questions relate to children's syntactic skills. Thirty-four mother-child dyads participated in a 15-min seminaturalistic play session. Children were between the ages of 5 and 7 years (M = 6.26 years, SD = 1.04 years; 20 girls/14 boys). The Diagnostic Evaluation of Language Variation (DELV) assessment was used to measure syntactic skills in children. Using the Systematic Analysis of Language Transcripts, questions were categorized based on structure (wh-questions vs. non-wh-questions) and purpose (information-seeking, pedagogical, or yes/no and rhetorical questions). A repeated-measures analysis of covariance and a linear regression model were implemented to address the frequency of different questions asked by mothers, as well as what types of questions are most related to children's concurrent syntactic skills. When controlling for total maternal utterances, results revealed that non-wh-questions and rhetorical/yes and no questions were the most frequent types of questions produced by mothers, in terms of structure and purpose, respectively. However, wh-questions were predominantly information-seeking questions. This is important, as the use of information-seeking wh-questions was positively associated with children's syntactic skills, as measured by the DELV, and resulted in children producing longer utterances in response to these questions, as determined by child mean length of utterance in words. Taken together, these findings suggest maternal use of wh-questions aids syntactic skills in children ages 5-7 years, likely because they require a more syntactically complex response on the child's behalf. https://doi.org/10.23641/asha.27276891.

Shifting the spotlight: What do we mean by ‘religious language’?

Abstract There are mainly two types of questions asked about religious language: those about identity (e.g., what is a religious language?) and those about meaning (e.g., what do its sentences say?). Most philosophers focus on the latter because while they disagree about meaning, they agree that some sentences are religious and that our understanding of them does not depend on us knowing what makes them religious. In this article, I provide two reasons why questions about identity should receive more attention. First, theories of identity and theories of meaning share a two-way relationship where the characteristics of one influence those of the other, and so overlooking identity overlooks important characteristics of meaning. Second, the study of religious language has been shaped by this relationship for some time and being aware of it improves our understanding of conventional trends and contemporary debates. If successful, this article will motivate philosophers to reconsider the role of identity in research and to dedicate more effort to its study.

A guideline-informed language model for paediatric cardiology demonstrates high performance in answering complex medical questions

Abstract Background Paediatric cardiology presents unique challenges with its diverse and complex cases, limited evidence base, and the necessity for multi-expert involvement in decision-making processes. In this context, the introduction of generative pre-trained transformer (GPT) based large language models (LLMs) offers a potential avenue for the provision of complex information and clinical decision support. Purpose This study evaluates the quality of three different GPT LLMs in answering complex medical questions, including a state-of-the-art preview model that incorporates the German paediatric cardiology guidelines. Methods Seven paediatric cardiologists and paediatric cardiac surgeons generated 72 questions, including complex questions and medical cases with associated questions. The questions were categorized by difficulty and required knowledge (factual and experience-based or mostly experience-based). We prompted the questions to three LLMs: GPT 3.5, GPT 4 and a GPT 4 turbo preview. The GPT 4 turbo preview was customized by incorporating all guidelines from the German Society for Paediatric Cardiology by a retrieval function. Employing one complex instruction for all questions, we prompted the LLMs to provide precise and detailed expert-level responses. The responses from each model were evaluated by experts based on relevance, factual accuracy, severity of possible harm, completeness, superfluous content, and age-related appropriateness from 0 (very bad) to 7 (very good). Differences were calculated using the Kruskal-Wallis-test in SPSS Version 28. Results Our findings indicated a good performance of all models regarding the dimensions tested. The figures show the average ratings (Figure 1, Figure 2A) and highlight significant differences after Bonferroni correction in bold (Figure 2B). The GPT 4 turbo preview, including the retrieval of guidelines, provided significantly more relevant (average rating [AR] 5.94, meaning mostly relevant), accurate (AR 5.6, meaning between somewhat and mostly accurate) and complete (AR 5, meaning fairly complete) answers compared to GPT 3.5 and GPT 4. In terms of difficulty levels or the type of questions, there was no significant difference in rating. Relevance ratings were slightly better in factual questions (AR 5.7) than in those requiring more experience-based knowledge (AR 5,3). Although GPT4 had higher average scores compared to GPT 3.5 in all dimensions except superfluous content, the differences in rating were not statistically significant. All models had relevant difficulties considering the age-related aspects of the questions (AR 4.06-4.45, p=0.455). Conclusion This study highlights the potential and limitations of AI language models in addressing complex medical questions in fields characterized by highly individualized decision-making scenarios. The findings advocate for the development of more specialized AI tools in medicine, tailored to specific medical fields and patient age groups.Fig 1:Average ratings of LLMsFig 2:Rating differences between LLMs

Technology-assisted instruction with teacher prompts on fraction multiplication word problems: A single-case design with visual analysis and Bayesian multilevel modeling

ABSTRACT This study examines the effects of technology-assisted instruction with teacher prompts on the ability to visualize and solve fraction multiplication word problems for four middle school students with learning disabilities. A multiple-probe design across participants, a type of single-case design, showed a functional relationship between the intervention and the targeted mathematical outcomes. Although there were some fluctuations over time, students demonstrated improvements from the baseline to intervention phases (Tau ranged from 0.76 to 1.00 for visualization and was 1.00 for problem-solving). Researchers employed Bayesian cumulative link mixed effects models to examine the moderating effects of word problem question types. Students showed greater maintenance effects on problem-solving than on visualization tasks, as reflected in changes in level (logit coefficient = 2.6) and trend (logit coefficient = 0.22). Students and teachers perceived vocabulary and multiplication fact practices, as well as the cognitive and metacognitive features embedded in the technology-assisted intervention, to be useful in learning targeted mathematics concepts. This study underscores the role of technology integration in enhancing teachers’ instructional approach and in aiding students’ acquisition and retention of mathematical concepts and skills.

A comparison of drug information question responses by a drug information center and by ChatGPT.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. A study was conducted to assess the accuracy and ability of Chat Generative Pre-trained Transformer (ChatGPT) to systematically respond to drug information inquiries relative to responses of a drug information center (DIC). Ten drug information questions answered by the DIC in 2022 or 2023 were selected for analysis. Three pharmacists created new ChatGPT accounts and submitted each question to ChatGPT at the same time. Each question was submitted twice to identify consistency in responses. Two days later, the same process was conducted by a fourth pharmacist. Phase 1 of data analysis consisted of a drug information pharmacist assessing all 84 ChatGPT responses for accuracy relative to the DIC responses. In phase 2, 10 ChatGPT responses were selected to be assessed by 3 blinded reviewers. Reviewers utilized an 8-question predetermined rubric to evaluate the ChatGPT and DIC responses. When comparing the ChatGPT responses (n = 84) to the DIC responses, ChatGPT had an overall accuracy rate of 50%. Accuracy across the different question types varied. In regards to the overall blinded score, ChatGPT responses scored higher than the responses by the DIC according to the rubric (overall scores of 67.5% and 55.0%, respectively). The DIC responses scored higher in the categories of references mentioned and references identified. Responses generated by ChatGPT have been found to be better than those created by a DIC in clarity and readability; however, the accuracy of ChatGPT responses was lacking. ChatGPT responses to drug information questions would need to be carefully reviewed for accuracy and completeness.

Impact of modality and mode of questioning and testing on memory reports

IntroductionIndividuals' memories are assessed in multiple contexts; however, depending on the context, how an individual is questioned may impact the quantity and quality of the details reported. One goal of this study is to investigate how the modality of questioning (individuals talk or write about an event) impacts memory reports. Additionally, being tested on previously learned information improves memory for that information compared to re-studying it. Consequently, another goal is to examine how questioning impacts memory reports compared to a second exposure. We utilized open-ended and pointed questions (true and false).MethodParticipants watched a short video and were questioned (Experiment 1: In-Person; Experiment 2: Virtual) about its contents immediately, 1 week, and 1 month later.ResultsThe current study found that writing leads to better quality memory reports than speaking, and the benefit is present 1 week later. Additionally, we found that writing mitigates an anticipated testing benefit, although this depended on whether a pointed or open-ended question was asked. Restudying (vs. immediate testing) led to better performance for the false pointed questions. However, the better performance operated differently depending on whether participants wrote or spoke following restudying, perhaps due to a differential criterion shift between the Restudy-Written and the Restudy-Spoken conditions.DiscussionWe conclude that the impact of the modality of questioning is influenced in several ways by the types of questions asked, which bears significance for many domains because one modality (or a combination) may be more suitable for producing more accurate memory reports as a function of different domains.

Development of the Web Application to Support the Process of Conducting Intellectual Games

The article discusses technologies for developing the web application designed to accompany the process of conducting an intellectual game in the format of an interactive quiz. An analysis of similar applications was carried out, which showed that none of them satisfies all the criteria essential in this situation. Requirements for the web application have been determined: the ability to create a library of quizzes, various types of questions, edit ready-made quizzes, participants enter answers through their devices online, award points for the correctness and speed of answers, display questions on the presenter's screen and on team devices, view intermediate and final results in the form of a list, returning participants to the game if necessary, saving the points received. The process of developing an optimized user interface using HTML, CSS, JavaScript, which allows users to interact with the web application, is described, the structure of the web application, the main forms of the administrator and game participants are presented. The server side of the application was developed using Node.JS technologies, including the Socket.io library, and the MongoDB database, the resulting collection of non-relational database is shown. To implement the functionality of the application pages, JavaScript was used; examples of codes are presented that implement the mechanism for connecting the presenter to the game, retrieving information from the database, recording the team's response, and awarding points for the correctness and speed of the response. The web application allows you to reduce the time spent by event organizers and participants and makes it possible to improve the organization of work in general. The presented web application for accompanying intellectual games was successfully approbated during events at the Nizhny Tagil State Social-Pedagogical Institute (branch) of the Russian State Vocational Pedagogical University. The materials of the article can serve as practical recommendations for the development of such web applications to accompany intellectual games held in the format of interactive quizzes.

Enhancing smartphone security with human centric bimodal fallback authentication leveraging sensors.

Smartphones store valuable personal information, necessitating robust authentication methods to protect user data. This research proposes a lightweight bi-model fallback authentication technique that combines dynamic security questions and finger pattern recognition using inertial measurement units. The dynamic security questions are generated based on the smartphone's usage behavior, while the owner's finger movements are captured using four different inertial sensors: accelerometer, gyroscope, gravity sensor, and magnetometer. By combining the answers to the questions and the owner's finger movements, the user can be authenticated even if the primary authentication method fails. In this study, data was collected from 24 participants, including 12 primary phone users and 12 close adversaries, over a span of 28 days. The dynamic security questions, derived from call, SMS, battery charging events, application usage, location, and physical activity categories, achieved high accuracy rates, with call, SMS, and application usage surpassing . Incorporating the inertial measurement units significantly improved the accuracy of all question types, increasing from a maximum of to , while also enhancing the True Positive Rate from 0.79 to 0.99 compared to a previous study. This research presents a promising lightweight bi-model fallback authentication technique that leverages dynamic security questions and inertial measurement units data, demonstrating its effectiveness for enhancing smartphone security.

Comparative Analysis of Large Language Models' Performance in Breast Imaging

Aim: To evaluate the performance of the flagship models, OpenAI's GPT-4o and Anthropic's Claude 3.5 Sonnet, in breast imaging cases. Materials and Methods: The dataset consisted of cases from the publicly available Case of the Month archive by the Society of Breast Imaging. Questions were classified as text-based or containing images from mammography, ultrasound, magnetic resonance imaging, or hybrid imaging. The accuracy rates of GPT-4o and Claude 3.5 Sonnet were compared using the Mann-Whitney U test. Results: Of the total 94 questions, 61.7% were image-based. The overall accuracy rate of GPT-4o was higher than that of Claude 3.5 Sonnet (75.4% vs. 67.7%, p=0.432). GPT-4o achieved higher scores on questions based on ultrasound and hybrid imaging, while Claude 3.5 Sonnet performed better on mammography-based questions. In tumor group cases, both models reached higher accuracy rates compared to the non-tumor group (both, p&gt;0.05). The models' performance in breast imaging cases overall exceeded 75%, ranging between 64-83% for questions involving different imaging modalities. Conclusion: In breast imaging cases, although GPT-4o generally achieved higher accuracy rates than Claude 3.5 Sonnet in image-based and other types of questions, their performances were comparable.

Analysis Of The Marketing Mix And Its Influence On Purchasing Decisions On The Prasetya Products

This study aims to identify, study and analyze the marketing mix of The Prasetya and The Influences in Customer Decisions to by product of The Prasetya. This study used qualitative research methods, with data collection techniques observation, interviews and explore theh types of open-ended questions where information is free to provide in depth information to be used as research data. The data analyzed is the result of interviews with employees, customers and experienced human resourch of UMKM using analyctical techniques including data reduction, data presentation and levers or cunclusions. The result of this study that marketing mix of The Prasetya has been able to influence consumer purchasing decisions and increase sales turnover and customers always make repeat purchases for the product and also increase the company's profits so that the company's goals can be achieved.

How We Communicate Forgiveness to Our Partners Matters: Forgiveness-Granting Strategies, Forgiveness Tendency, Commitment, and Relationship Satisfaction in Dating and Married Couples

Abstract Individuals in dating and marital relationships experience various transgressions that require forgiveness (e.g., hurtful communication, mistrust, lies, or infidelity). This study examines forgiveness-granting strategies in the context of forgiveness tendency, relationship length, commitment, satisfaction, and relational consequences to better understand relationship dynamics. 649 individuals (532 dating, 117 married), aged 18–65 (M = 26.00, SD = 8.82) participated. The sample included 517 women (79.7 %) and 132 men (20.3 %). Participants described a forgiven transgression and completed questionnaires, including the Multidimensional Forgiveness-Granting Scale (MFGS), Transgression-Related Interpersonal Motivations Inventory (TRIM-18), Relationship Assessment Scale (RAS), and the commitment subscale from the Investment Model Scale. One open-ended question (types of forgiven transgressions) was analyzed consensually. Quantitative data were analyzed using correlational analysis, regression analysis, and t-tests. The most common transgression was infidelity. A linear regression analysis showed that the strongest positive predictor of relationship satisfaction was the tendency to forgive one’s partner. Nonverbal displays positively predicted relationship strengthening, while the discussion strategy predicted relationship deterioration negatively. These findings emphasize the importance of how forgiveness is communicated and may inform interventions to enhance romantic relationships.

Types of Questions Asked by Teachers at Primary School 077786 Tuhembaruzo in Classroom Interaction

This study aims to analyze the types of teacher questions in the teaching and learning process in three study groups and to analyze student activeness in the learning process at SD Negeri 077786 Tuhembaruzo. To obtain the results of this research, a descriptive qualitative method was used because this research focuses on phenomena that occur in the classroom. After analyzing it was found that there were 3 types of questions used by teachers in the study groups, namely procedural, convergent and divergent types of questions. the type of teacher questions in the three study groups at SD Negeri 077786 Tuhembaruzo was more convergent type than divergent and procedural types, namely 57, 23% of questions. While the teacher's procedural type questions amounted to 19.07% and the divergent type amounted to 23.68%.