Case-based Strategies Research Articles

Effects of Case-based Strategy on Academic Achievement in Mathematics Algebraic Word Problems among Junior Secondary School Students in Ibadan Metropolis, Oyo State, Nigeria

This study investigated the Effect of Case-based Strategy on Academic Achievement in Mathematics Word Problems among Junior Secondary School Students in Ibadan Metropolis, Oyo State, Nigeria. The research focused on evaluating learning outcomes, knowledge retention, and overall students’ performance when exposed to this teaching approach based on constructivism and behaviorism theories of learning. The study employed a quasi-experimental research design. The population of the study consisted of all 20244 Junior Secondary School students in Oyo State, while two intact classes of 68 JSS2 students participated in the study. Two lesson plans and a validated Mathematics Achievement Test (MAT) were used as instruments for data collection. The MAT was tested for reliability having a value of 0.85 and the data generated was statistically analyzed using frequency counts, percentages, standard deviation and Analysis of Co-variance (ANCOVA) at a significance level of 0.05. The findings revealed that the effect of case-based strategy on students’ academic achievement was significant (F(1,65) = 72.771, p< 0.05) and was found to be more effective in enhancing students’ academic achievement in algebraic word problems. It was recommended that educators should incorporate case-based strategies in teaching Mathematics Algebraic word problem at the Junior Secondary School for effective outcome.

China's prevention and control experience of echinococcosis: A 19-year retrospective.

Echinococcosis poses a significant threat to public health. The Chinese government has implemented prevention and control measures to mitigate the impact of the disease. By analyzing data from the Chinese Center for Disease Control and Prevention and the State Council of the People's Republic of China, we found that implementation of these measures has reduced the infection rate by nearly 50% between 2004 to 2022 (from 0.3975 to 0.1944 per 100,000 person-years). Nonetheless, some regions still bear a significant disease burden, and lack of detailed information limites further evaluation of the effects on both alveolar and cystic echinococcosis. Our analysis supports the continuing implementation of these measures and suggests that enhanced wildlife management, case-based strategies, and surveillance systems will facilitate disease control.

Measurement Strategies for The Joint Commission Health Care Disparities Standard: Defining Hospital-Based Requirements—Part 1

Measurement Strategies for The Joint Commission Health Care Disparities Standard: Defining Hospital-Based Requirements—Part 1

Application of Case-Based Readiness Assurance Process as a Model for Case-Based Pedagogy and Collaborative Learning in Physiology.

The preclinical phase of the undergraduate medical curriculum has to embed clinically relevant learning experience to bridge basic sciences with clinical disciplines. Student-centric educational methods like the readiness assurance process of team-based learning promote active learning. In this study, we report our implementation of the case-based readiness assurance process (CBRAP) as a case-based strategy for introducing early clinical exposure in the preclinical phase of the undergraduate medical curriculum in India. Four CBRAPs with individual and group readiness assurance tests (IRAT and GRAT) were conducted in four different systems taught in physiology (hematology, muscle physiology, cardiovascular physiology, and renal physiology). The multiple-choice questions for CBRAP were specifically designed to test application and problem-solving by incorporating clinical vignettes with pathophysiology and lab findings. This study was designed to involve all 250 students from the first professional year. The GRAT scores were significantly more than mean IRAT scores in all four CBRAPs (p value < 0.001). The GRAT scores in the second, third, and fourth CBRAPs were significantly better than the GRAT score of the first CBRAP (p value < 0.001). The GRAT scores correlated significantly with mean IRAT in three out of four CBRAPs and with the highest IRAT in two out of four CBRAPs. Based on the student feedback of CBRAP and other case-based strategies, it was found that students preferred CBRAP and the majority of students reported that discussion of CBRAP questions with team members was useful. In conclusion, innovative case-based teaching methods with active student involvement can be incorporated in the preclinical curriculum for improving learning outcomes.

RELATIVE EFFECTIVENESS OF CASE-BASED AND COLLABORATIVE LEARNING STRATEGIES ON STUDENTS’ ACHIEVEMENT AND RETENTION IN SENIOR SECONDARY SCHOOL PHYSICS

This study investigated the relative effectiveness of case-based and collaborative learning strategies on students’ achievement and retention in senior secondary school physics. The study adopted pretest, posttest control group design. Simple random sampling technique was used to select three schools used for the study. The sample used for the study was eighty five (85) senior secondary two (SS 2) physics students randomly selected from the three schools in Ileoluji/Okeigbo Local Government Area of Ondo State, Nigeria. The study made use of Physics Achievement Test (PAT) with internal consistency of 0.84 using Kuder Richardson Formular 21. The data collected were analysed using Analysis of Covariance and Scheffe post hoc analysis was used to obtain the direction of significance. From the findings, it was observed that, learning strategies had significant main effect on students’ achievement (F (2,82) = 134.97, p = 0.000) and retention (F (2,82) = 20.67, p = .000) in the concept of optics in physics. The results of the Scheffe post hoc analysis indicated that, case-based learning strategy was the most effective in facilitating students’ achievement and retention in the concept of optics. This was followed by collaborative learning strategy while conventional learning strategy was found to be the least facilitative. Conclusion from the findings led to the recommendation that, teachers should be encouraged to adopt the use of case-based and collaborative learning strategy in teaching the concept of optics in physics in order for the students to develop problem solving skills, construction of knowledge and student-centred activities. Article visualizations:

Promoting Learning Using Case-Based Strategies in Nursing Professional Development.

Realistic situations can be used to develop a variety of learning activities, including case reports, standard and evolving case studies, and problem-based learning. Most case-based strategies are aimed at promoting learner interaction, problem solving, and collaborative learning. This article provides a description and discussion of how each can be applied. Hints for developing the different types of cases are included, followed by specific examples.

Instructional Strategies Used to Improve Students’ Comfort and Skill in Addressing the Occupational Therapy Process

The purpose of this study was to investigate the effectiveness of an intentional blending of instructional strategies in an occupational therapy (OT) entry-level master’s course. The OT Adult Practice course uses case-based instructional strategies, clinical skills labs, and standardized patient experiences in a dovetailed approach across three progressively complex clinical scenarios involving adult clients. The course is designed to support students in addressing the entire OT Process. Results of quantitative data analysis indicated that the sequential application of case-based instructional strategies, lab experiences, and standardized patient learning opportunities significantly improved students’ self-perception of their level of comfort and skill in being able to perform the following components of the OT process for adult clients: occupational profile, OT evaluation, developing an OT treatment plan, implementing OT treatment, and planning for discharge.

Six strategies for generalizing software engineering theories

General theories of software engineering must balance between providing full understanding of a single case and providing partial understanding of many cases. In this paper we argue that for theories to be useful in practice, they should give sufficient understanding of a sufficiently large class of cases, without having to be universal or complete. We provide six strategies for developing such theories of the middle range.In lab-to-lab strategies, theories of laboratory phenomena are developed and generalized to other laboratory phenomena. This is a characteristic strategy for basic science. In lab-to-field strategies, theories are developed of artifacts that first operate under idealized laboratory conditions, which are then scaled up until they can operate under uncontrolled field conditions. This is the characteristic strategy for the engineering sciences.In case-based strategies, we generalize about components of real-world cases, that are supposed to exhibit less variation than the cases as a whole. In sample-based strategies, we generalize about the aggregate behavior of samples of cases, which can exhibit patterns not visible at the case level. We discuss three examples of sample-based strategies.Throughout the paper, we use examples of theories and generalization strategies from software engineering to illustrate our analysis. The paper concludes with a discussion of related work and implications for empirical software engineering research.

Case-based strategies for argumentation dialogues in agent societies

In multi-agent systems, agents perform complex tasks that require different levels of intelligence and give rise to interactions among them. From these interactions, conflicts of opinion can arise, especially when these systems become open, with heterogeneous agents dynamically entering or leaving the system. Therefore, agents willing to participate in this type of system will be required to include extra capabilities to explicitly represent and generate agreements on top of the simpler ability to interact. Furthermore, agents in multi-agent systems can form societies, which impose social dependencies on them. These dependencies have a decisive influence in the way agents interact and reach agreements. Argumentation provides a natural means of dealing with conflicts of interest and opinion. Agents can reach agreements by engaging in argumentation dialogues with their opponents in a discussion. In addition, agents can take advantage of previous argumentation experiences to follow dialogue strategies and persuade other agents to accept their opinions. Our insight is that case-based reasoning can be very useful to manage argumentation in open multi-agent systems and devise dialogue strategies based on previous argumentation experiences. To demonstrate the foundations of this suggestion, this paper presents the work that we have done to develop case-based dialogue strategies in agent societies. Thus, we propose a case-based argumentation framework for agent societies and define heuristic dialogue strategies based on it. The framework has been implemented and evaluated in a real customer support application.

An Investigation of Case-Based Instructional Strategies on Learning, Retention, and Ethical Decision-Making

Case-based instruction has been successfully employed by educators across various fields; however, little is known about how individuals work with cases during the learning process. We examined two well-established instructional strategies: elaboration and self-development of narratives. Participants were randomly assigned to (1) elaborate on a given case, (2) develop their own case, (3) elaborate on a self-developed case, or (4) a control condition. Findings indicated that those who elaborated on a given case and the control group outperformed the other treatment groups in terms of case-based knowledge acquisition, execution of sensemaking processes, utilization of ethical decision-making (EDM) strategies, and performance on two EDM measures. Implications for use of instructional strategies in ethics training programs are discussed.

Case-based strategies in computer poker

The state-of-the-art within Artificial Intelligence has directly benefited from research conducted within the computer poker domain. One such success has been the advancement of bottom up equilibrium finding algorithms via computational game theory. On the other hand, alternative top down approaches, that attempt to generalise decisions observed within a collection of data, have not received as much attention. In this work we employ a top down approach in order to construct case-based strategies within three computer poker domains. Our analysis begins within the simplest variation of Texas Hold'em poker, i.e. two-player, limit Hold'em. We trace the evolution of our case-based architecture and evaluate the effect that modifications have on strategy performance. The end result of our experimentation is a coherent framework for producing strong case-based strategies based on the observation and generalisation of expert decisions. The lessons learned within this domain offer valuable insights, that we use to apply the framework to the more complicated domains of two-player, no-limit Hold'em and multi-player, limit Hold'em. For each domain we present results obtained from the Annual Computer Poker Competition, where the best poker agents in the world are challenged against each other. We also present results against human opposition.

Multi-strategy workspace navigation for design education

Technical teaching at universities has not successfully integrated recent advances in cognitive sciences, design studies and information technology into design education. Since industry needs engineers that are immediately productive and creative, universities are revising their priorities in order to improve the decision making skills of future engineers. In this paper, knowledge from multiple sources, a navigation framework and specially developed interactive features are integrated into FIBRES. FIBRES is a decision making pilot software for design education in the area of bridge engineering. To help students learn productive and creative multi-strategy design, it is best to delay introducing case-based strategies.

Types of Case Study Work: A Conceptual Framework for Case-Based Research

This article describes a conceptual framework for understanding the phases of case-based research. Case-based strategies in research are widely used in case study methodology as well as in a number of qualitative methodologies, including grounded theory development, phenomenological research method, and psychotherapy process research. The epistemological principles on which casebased research is based are fundamentally different from those that inform group-based research using quantitative multivariate statistics. The case-based research process is divided into three genieral phases: descriptive, theoretical-heuristic, and theory testing. Each of these phases is subdivided into two categories. The aims and epistemological principles related to each phase are discussed and illustrated with examples from contemporary research. The principles for establishing validity in case-based research are also reviewed and, to assist research students and supervisors, some common pitfalls are noted. The article shows that rigorous work with single caLses or series of cases using case-based principles and methodology is indeed, as Bromley claimed, "the bedrock of scientific investigation."

Case-based strategies for competitive advantage

Case-based strategies for competitive advantage

Strategies of failure diagnosis in computer-controlled manufacturing systems: empirical analysis and implications for the design of adaptive decision support systems

This study investigates strategies in failure diagnosis at cutting-machine-tools with a verbal knowledge acquisition technique. Sixty-nine semi-structured interviews were performed with mechanical and electrical maintenance technicians, and a protocol analysis was conducted. Strategies were analysed in dependence of the technician's job experience, his familiarity with the problem and problem complexity. The technicians were categorized into three groups, novices, advanced, and experts, based upon level of experience. Results show that typical strategies of failure diagnosis are "Historical information", "Least effort", "Reconstruction", and "Sensory check". Strategies that lead to a binary reduction of the problem space, such as "Information uncertainty" and "Split half", play only a minor role in real-life failure diagnosis. Job experience and the familiarity with the problem significantly influenced the occurrence of strategies. In addition to "Symptomatic search" and "Topographic search", results show frequent use of case-based strategies, particularly in routine failures. In novel situations, technicians usually used "Topographic search". A software design method, the strategy-based software design (SSD) is proposed, that uses strategies to derive decision support systems, that are adaptive to the different working styles and the changing levels of experience in user groups. The methodology is briefly described and illustrated by the development of an information support system for maintenance and repair.