Developing a Cost-Effective Surgical Scheduling System Applying Lean Thinking and Toyota's Methods for Surgery-Related Big Data for Improved Data Use in Hospitals: User-Centered Design Approach

BACKGROUND

Surgical scheduling is pivotal in managing daily surgical sequences, impacting patient experience and hospital resources significantly. With operating rooms costing approximately US $36 per minute, efficient scheduling is vital. However, global practices in surgical scheduling vary, largely due to challenges in predicting individual surgeon times for diverse patient conditions. Inspired by the Toyota Production System's efficiency in addressing similar logistical challenges, we applied its principles as detailed in the book "Lean Thinking" by Womack and Jones, which identifies processes that do not meet customer needs as wasteful. This insight is critical in health care, where waste can compromise patient safety and medical quality.

OBJECTIVE

This study aims to use lean thinking and Toyota methods to develop a more efficient surgical scheduling system that better aligns with user needs without additional financial burdens.

METHODS

We implemented the 5 principles of the Toyota system: specifying value, identifying the value stream, enabling flow, establishing pull, and pursuing perfection. Value was defined in terms of meeting the customer's needs, which in this context involved developing a responsive and efficient scheduling system. Our approach included 2 subsystems: one handling presurgery patient data and another for intraoperative and postoperative data. We identified inefficiencies in the presurgery data subsystem and responded by creating a comprehensive value stream map of the surgical process. We developed 2 Excel (Microsoft Corporation) macros using Visual Basic for Applications. The first calculated average surgery times from intra- or postoperative historic data, while the second estimated surgery durations and generated concise, visually engaging scheduling reports from presurgery data. We assessed the effectiveness of the new system by comparing task completion times and user satisfaction between the old and new systems.

RESULTS

The implementation of the revised scheduling system significantly reduced the overall scheduling time from 301 seconds to 261 seconds (P=.02), with significant time reductions in the revised process from 99 seconds to 62 seconds (P<.001). Despite these improvements, approximately 21% of nurses preferred the older system for its familiarity. The new system protects patient data privacy and streamlines schedule dissemination through a secure LINE group (LY Corp), ensuring seamless flow. The design of the system allows for real-time updates and has been effectively monitoring surgical durations daily for over 3 years. The "pull" principle was demonstrated when an unplanned software issue prompted immediate, user-led troubleshooting, enhancing system reliability. Continuous improvement efforts are ongoing, except for the preoperative patient confirmation step, which requires further enhancement to ensure optimal patient safety.

CONCLUSIONS

Lean principles and Toyota's methods, combined with computer programming, can revitalize surgical scheduling processes. They offer effective solutions for surgical scheduling challenges and enable the creation of a novel surgical scheduling system without incurring additional costs.

Sorption Behavior of Azo Dye Congo Red onto Activated Biochar from Haematoxylum campechianum Waste: Gradient Boosting Machine Learning-Assisted Bayesian Optimization for Improved Adsorption Process

This work aimed to describe the adsorption behavior of Congo red (CR) onto activated biochar material prepared from Haematoxylum campechianum waste (ABHC). The carbon precursor was soaked with phosphoric acid, followed by pyrolysis to convert the precursor into activated biochar. The surface morphology of the adsorbent (before and after dye adsorption) was characterized by scanning electron microscopy (SEM/EDS), BET method, X-ray powder diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR) and, lastly, pHpzc was also determined. Batch studies were carried out in the following intervals of pH = 4-10, temperature = 300.15-330.15 K, the dose of adsorbent = 1-10 g/L, and isotherms evaluated the adsorption process to determine the maximum adsorption capacity (Qmax, mg/g). Kinetic studies were performed starting from two different initial concentrations (25 and 50 mg/L) and at a maximum contact time of 48 h. The reusability potential of activated biochar was evaluated by adsorption-desorption cycles. The maximum adsorption capacity obtained with the Langmuir adsorption isotherm model was 114.8 mg/g at 300.15 K, pH = 5.4, and a dose of activated biochar of 1.0 g/L. This study also highlights the application of advanced machine learning techniques to optimize a chemical removal process. Leveraging a comprehensive dataset, a Gradient Boosting regression model was developed and fine-tuned using Bayesian optimization within a Python programming environment. The optimization algorithm efficiently navigated the input space to maximize the removal percentage, resulting in a predicted efficiency of approximately 90.47% under optimal conditions. These findings offer promising insights for enhancing efficiency in similar removal processes, showcasing the potential of machine learning in process optimization and environmental remediation.

Corrigendum: Teaching programming and computational thinking in early childhood education: a case study of content knowledge and pedagogical knowledge

[This corrects the article DOI: 10.3389/fpsyg.2023.1252718.].

Teaching programming and computational thinking in early childhood education: a case study of content knowledge and pedagogical knowledge

Programming and computational thinking (CT) have been progressively incorporated into early childhood education to prepare children for the digital age. However, little is known about the content knowledge (CK) and pedagogical knowledge (PK) possessed by early childhood teachers in this domain. To address this gap, we conducted a case study of an early childhood teacher in China who had experience developing and implementing an unplugged programming and CT curriculum. The triangulation of data sources was established to collect evidence from videotaped observations, interviews, and lesson plans. For the CK, analysis of these findings revealed that the teacher had a more robust understanding of CT concepts (e.g., sequences, conditionals, and loops) compared to CT practices (e.g., decomposition, debugging) and CT perspectives (e.g., perseverance, choices of conduct). In terms of PK, the teacher could apply the general pedagogical knowledge but was relatively weak in using content-specific pedagogical knowledge. As the first endeavor to investigate an early childhood teacher's CK and PK in teaching programming and CT, this study provides significant implications for improving teachers' professional knowledge and teaching effectiveness in this burgeoning area.

Co-Learning Computational and Design Thinking Using Educational Robotics: A Case of Primary School Learners in Namibia

In a two-day educational robotics workshop in a Namibian primary boarding school, learners with no programming skills managed to apply both computational and design thinking skills with the aid of educational robotics. Educational robotics has proved to be an area which enhances learning both computational thinking and design thinking. An educational robotics (ER) workshop focusing on Arduino robotics technologies was conducted with primary school learners at Nakayale Private Academy. Observation methods through watching, listening and video recordings were used to observe and analyze how the learners were interacting throughout the workshop. Based on the results, it was concluded that this approach could be applied in classrooms to enable the primary school learners apply computational and design thinking in preparation of becoming the producers and not only the consumers of the 4IR technologies.

Migration of an Escape Room-Style Educational Game to an Online Environment: Design Thinking Methodology

Background

The COVID-19 pandemic outbreak has led to a sudden change in education, closing schools and shifting to online teaching, which has become an enormous challenge for teachers and students. Implementing adequate online pedagogical approaches and integrating different digital tools in the teaching process have become a priority in educational systems. Finding a way to keep students' interest and persistence in learning is an important issue that online education is facing. One possible way to establish engaging and interactive learning environments, using the energy and enthusiasm of students for educational purposes, is the use of game-based learning activities and gamification of different parts of the educational process.

Objective

This paper presents a use case of migrating an escape room–style educational game to an online environment by using the design thinking methodology. We wanted to show that the design thinking methodology is useful to create engaging and motivating online games that provide educational value.

Methods

Starting from students’ perspective, we created a simple digital escape room–style game where students got an opportunity to self-assess their knowledge in computer science at their own pace. Students tested this prototype game, and their opinions about the game were collected through an online survey. The test's goal was to evaluate the students' perceptions about the implemented digital escape room–style educational game and gather information about whether it could achieve students' engagement in learning computer science during online teaching.

Results

In total, 117 students from sixth and seventh grades completed the survey regarding the achieved student engagement. Despite the differences in students’ answers about game complexity and puzzle difficulty, most students liked the activity (mean 4.75, SD 0.67, on a scale from 1 to 5). They enjoyed the game, and they would like to participate in this kind of activity again (mean 4.74, SD 0.68). All (n=117, 100%) students found the digital escape room–style educational game interesting for playing and learning.

Conclusions

The results confirmed that digital escape room–style games could be used as an educational tool to engage students in the learning process and achieve learning outcomes. Furthermore, the design thinking methodology proved to be a useful tool in the process of adding novel educational value to the digital escape room–style game.

A multigroup structural equation modeling analysis of students' perception, motivation, and performance in computational thinking

Students' perceptions of learning are important predictors of their learning motivation and academic performance. Examining perceptions of learning has meaningful implications for instruction practices, while it has been largely neglected in the research of computational thinking (CT). To contribute to the development of CT education, we explored the influence of students' perceptions on their motivation and performance in CT acquisition and examined the gender difference in the structural model using a multigroup structural equation modeling (SEM) analysis. Two hundred and eighty-five students from a Chinese urban high school were recruited for the study. The analysis revealed that students' perceptions of CT positively influenced their CT performance and learning motivation, and some motivational constructs, namely self-efficacy and learning goal orientation (LGO), also positively influenced their CT performance. Furthermore, in the male student group, perceptions of CT exhibited significant correlations with both self-efficacy and LGO. However, no significant correlation was found in the female student group. Implications for research and teaching practice in CT education are presented herein.

Retrieval Practices Enhance Computational and Scientific Thinking Skills

The notion of teaching experts’ habits of mind (e.g., computational thinking and scientific thinking) to novices seems to have inspired many educators and researchers worldwide. In particular, a great deal of efforts has been invested in computational thinking (CT) and its manifestations in different fields. However, there remain some troubling spots in CT education as far as how to teach it at different levels of education. The same argument applies to teaching scientific thinking (ST) skills. A remedy has been suggested to narrow CT and ST skillsets down to core cognitive competencies so they can be introduced in early and middle grades and continue to be nurtured during secondary and post-secondary years. Neuroscientists suggest that the act of (computational) thinking is strongly linked to the acts of information storage/retrieval by our brain. Plus, years of research have shown that retrieval practices promote not only knowledge retention but also inductive reasoning and deductive reasoning. Not surprisingly, these reasoning skills are core elements of both CT and ST skillsets. This article will mesh the findings of a teacher professional development with the existing literature to lay a claim that retrieval practices enhance CT and ST skills. The study offered training to secondary school teachers (n = 275) who conducted classroom action research to measure the impact of retrieval practices on teaching and learning of STEM and CT concepts. We used a quasi-experimental research design with purposeful sampling and a sequential mixed-methods approach focusing on the impact of professional development on teacher outcomes and, in turn, on student outcomes. A survey of teacher participants showed that the majority (96%) of survey respondents (n = 232) reported a good understanding of retrieval strategies, and how relevant ideas can be implemented and tested in the classroom. A large number of action research (target-control) studies by teachers (n = 122) showed that students who learned STEM and CS concepts through retrieval practices consistently scored 5–30% higher than those using the usual blocked practice. In most cases, the difference was statistically significant (p < 0.05). While the study contributes to retrieval practices literature, those looking for best practices to teach core CT and ST skills should benefit from it the most. The study concludes with some recommendations for future research based on the limitations of its current findings.

Combined Effects of Block-Based Programming and Physical Computing on Primary Students' Computational Thinking Skills

Basic Digital Education (BDE) is already planned to be integrated with the forthcoming curriculum for Austrian primary schools (6–10 years) as it was already implemented for lower secondary schools (10–14 years) in 2018. BDE includes the most essential and novel developments of Computational Thinking (CT), which are fundamentally responsible for nurturing students' problem-solving skills. Thus, evaluating teaching materials, scaffolding guidelines, and assessments is becoming increasingly important for the successful implementation of CT in Austrian classrooms. This study is a part of a longitudinal multi-cycle educational design research project aiming to explore how to foster CT and to raise the awareness, importance, and confidence of teachers and students in applying CT for everyday uses. Our paper focuses on a sub-study in which teaching units for grade 3 and 4 students (8–10 years) were designed by combining an Open Educational Resource (OER) textbook and Physical Computing with the micro:bit device. The designed learning environment consists of three units and was implemented in two classes over 3 weeks. The two classes were further split into two groups each, to ensure better support during implementation. The class teachers received upfront teacher training and conducted pre- and post-test assessments with the students. The resulting data was then analyzed to gain insights into the effects on CT skills of the young learners. Results showed that combining block-based programming and physical computing devices could become a promising approach to promote computational thinking skills in lower school grades. Furthermore, the observed direction of the designed units supports low-barrier access to increase the desired uses of CT in classrooms.

Developing Teaching Practice in Computational Thinking in Palestine

Sporadic efforts have been made to introduce computational thinking methods into K-12 education in Palestine, but these have been held back by the challenging educational environment. However, a recent in-service training initiative, funded and organized by the Ministry or Education of Palestine, constitutes a significant effort to embed computational thinking in K-12 practice. The middle school teachers who participated in the training course were invited to participate in the present study, and 38 did so. A qualitative approach involving both interviews with teachers and classroom observations was used in data collection. All the teachers agreed to be observed in their classrooms, while 20 of the 38 also agreed to participate in the interviews. The findings showed that teachers of a range of topics, including social sciences and languages, employed computational thinking skills in teaching their students, but they were confronted by a number of challenges, including technical infrastructure and support, and a lack of time to prepare CT classes and space in the curriculum to deliver them. The results indicate that the most appropriate action to support teachers’ delivery of CT would be to provide peer exchanges and expert coaching in the integration of CT in the curriculum.

Integrating Computational Thinking and Empowering Metacognitive Awareness in Stem Education

Education digitization highly enthuses learners for deeper learning and developing thought processes in formulating problems and their solutions effectively in their real-life circumstances. Implementing computational thinking skills through programming in Malaysian primary and secondary school STEM curriculum create huge challenges, especially among STEM educators. This study highlights the integration of four major theories in developing the Metacognitive Empowerment by Computational Thinking (ME-CoT) learning module by cultivating computational thinking through programming skills to promote metacognitive awareness in Biology students. Pilot research was conducted to investigate the reliability of the ME-CoT learning module. Since the study sample was less than 30 students then, the consistency of the measurements, Pearson's r was calculated to identify stability reliability. Findings revealed that the ME-CoT learning module has very strong stability reliability with a value of r = 0.974 and provides advantages such as assisting students to understand the content of the lesson more actively and in a fun way.

iArm: Design an Educational Robotic Arm Kit for Inspiring Students' Computational Thinking

Educational robotics is an effective carrier of information technology education, making its way into classrooms. However, the design of the educational robotic arm kit and the study on the effect of robotic arms on students' thinking literacy remain to be completed. In this paper, iArm, a 6-DOF robotic arm consisting of a drive chassis, an arm body, and end tools, is presented. Its auxiliary modules, including the vision module and conveyor belt, and the curriculum targeting students' computational thinking are also developed to refine the current educational robotic arm kit. Furthermore, to explore the effectiveness of the iArm kit, thirteen high school students participated in the semester-long curriculum, completed assigned projects, and filled out the pre-test and post-test scales. By formative and summative evaluation, the result shows that the iArm kit effectively enhanced students' computational thinking.

Gender differential item functioning analysis in measuring computational thinking disposition among secondary school students

Computational thinking refers to the cognitive processes underpinning the application of computer science concepts and methodologies to the methodical approach and creation of a solution to a problem. The study aims to determine how students' cognitive, affective, and conative dispositions in using computational thinking are influenced by a gender. This study used a survey research design with quantitative approach. Five hundred thirty-five secondary school students were sampled using probability sampling with the Computational Thinking Disposition Instrument (CTDI). WINSTEPS version 3.71.0 software was subsequently employed to assess the Gender Differential item functioning (GDIF) including reliability and validity with descriptive statistics were employed to assess students' disposition toward practicing computational thinking. In addition to providing implications for the theory, the data give verifiable research that the CT disposition profile consists of three constructs. In addition, the demonstrated CTDI has good GDIF features, which may be employed to evaluate the efficacy of the application of CT in the Malaysian curriculum by measuring the level of CT in terms of the disposition profile of students.

Effects of the Problem-Oriented Learning Model on Middle School Students' Computational Thinking Skills in a Python Course

The rapid development of computers and technology affects modern daily life. Individuals in the digital age need to develop computational thinking (CT) skills. Existing studies have shown that programming teaching is conducive to cultivating students' CT, and various learning models have different effects on the cultivation of CT. This study proposed a problem-oriented learning (POL) model that is closely related to programming and computational thinking. In all, 60 eighth-grade students from a middle school in China were divided into an experimental group (EG) which adopted the POL model, and a control group (CG) which adopted the lecture-and-practice (LAP) learning model. The results showed that the students who were instructed using the POL model performed better than those who were instructed using the LAP model on CT concepts, CT practices, and CT perspectives. Significant differences were found for CT concepts and CT perspectives, but not for CT practices. Findings have implications for teachers who wish to apply new learning models to facilitate students' CT skills, and the study provides a reference case for CT training and Python programming teaching.

Educational Robotics and Tangible Devices for Promoting Computational Thinking

Recently, efforts have been made to add programming activities to the curriculum that promote computational thinking and foster 21st-century digital skills. One of the programming modalities is the use of Tangible Programming Languages (TPL), used in activities with 4+ year old children. In this review, we analyze solutions proposed for TPL in different contexts crossing them with non-TPL solutions, like Graphical Programming Languages (GPL). We start to characterize features of language interaction, their use, and what learning activities are associated with them. Then, in a diagram, we show a relation between the complexity of the languages with factors such as target age and output device types. We provide an analysis considering the type of input (e.g., TPL versus GPL) and output devices (e.g., physical robot versus graphical simulation) and evaluate their contribution to further insights about the general trends with respect to educational robotic systems. Finally, we discuss the opportunities to extend and improve TPLs based on the different solutions identified.

Developing Computational Thinking Teaching Strategies to Model Pandemics and Containment Measures

COVID-19 has been extremely difficult to control. The lack of understanding of key aspects of pandemics has affected virus transmission. On the other hand, there is a demand to incorporate computational thinking (CT) in the curricula with applications in STEM. However, there are still no exemplars in the curriculum that apply CT to real-world problems such as controlling a pandemic or other similar global crises. In this paper, we fill this gap by proposing exemplars of CT for modeling the pandemic. We designed exemplars following the three pillars of the framework for CT from the Inclusive Mathematics for Sustainability in a Digital Economy (InMside) project by Asia-Pacific Economic Cooperation (APEC): algorithmic thinking, computational modeling, and machine learning. For each pillar, we designed a progressive sequence of activities that covers from elementary to high school. In an experimental study with elementary and middle school students from 2 schools of high vulnerability, we found that the computational modeling exemplar can be implemented by teachers and correctly understood by students. We conclude that it is feasible to introduce the exemplars at all grade levels and that this is a powerful example of Science Technology, Engineering, and Mathematics (STEM) integration that helps reflect and tackle real-world and challenging public health problems of great impact for students and their families.

Development of a Pandemic Awareness STEM Outreach Curriculum: Utilizing a Computational Thinking Taxonomy Framework

Computational thinking is an essential skill in the modern global workforce. The current public health crisis has highlighted the need for students and educators to have a deeper understanding of epidemiology. While existing STEM curricula has addressed these topics in the past, current events present an opportunity for new curricula that can be designed to present epidemiology, the science of public health, as a modern topic for students that embeds the problem-solving and mathematics skills of computational thinking practices authentically. Using the Computational Thinking Taxonomy within the informal education setting of a STEM outreach program, a curriculum was developed to introduce middle school students to epidemiological concepts while developing their problem-solving skills, a subset of their computational thinking and mathematical thinking practices, in a contextually rich environment. The informal education setting at a Research I Institution provides avenues to connect diverse learners to visually engaging computational thinking and data science curricula to understand emerging teaching and learning approaches. This paper documents the theory and design approach used by researchers and practitioners to create a Pandemic Awareness STEM Curriculum and future implications for teaching and learning computational thinking practices through engaging with data science.

The Neural Correlates of Computational Thinking: Collaboration of Distinct Cognitive Components Revealed by fMRI

Recent technical advance attracts great attention to the promotion of programming skills, in particular, and computational thinking (CT), in general, as a new intellectual competency. However, the understanding of its cognitive substrates is limited. The present study used functional magnetic resonance imaging to examine the neural correlates of programming to understand the cognitive substrates of CT. Specifically, magnetic resonance imaging signals were collected while the participants were mentally solving programming problems, and we found that CT recruited distributed cortical regions, including the posterior parietal cortex, the medial frontal cortex, and the left lateral frontal cortex. These regions showed extensive univariate and multivariate resemblance with arithmetic, reasoning, and spatial cognition tasks. Based on the resemblance, clustering analyses revealed that cortical regions involved in CT can be divided into Reasoning, Calculation, Visuospatial, and Shared components. Further, connectivity increased during programming within the CT network constructed by these four components and decreased between the CT network and other cortical regions. In sum, our study revealed the cognitive components underlying CT and their neural correlates and further suggests that CT is not a simple sum of parallel cognitive processes, but a composite cognitive process integrating a set of intellectual abilities, particularly those in the science, technology, engineering, and math domains.

A New Application in Biology Education: Development and Implementation of Arduino-Supported STEM Activities

Considering that generations that have grown up in the 21st-century have grown alongside technology, it is thought that integrating technology into lessons helps students learn the subject. This study aims to develop five STEM activities for the lesson of the human body systems by integrating the coding-based Arduino into STEM education. The activities were implemented to 6th-grade students for seven weeks and the effects on students' skills of establishing a cause-effect relationship. The study method was pre-test-post-test quasi-experimental design, and the cause-effect relationship scale and semi-structured view form were used as data collection tools. As a result of the study, a significant difference was found between the Arduino-supported STEM activities developed and the students' skills of establishing a cause-effect relationship. The students who received the Arduino-supported STEM education found the course to be entertaining and educational, and the future goals of these students were affected. In order to bring individuals who love their profession into the future, Arduino-supported STEM education should be applied and expanded in other branches and class levels.

Does learning to code influence cognitive skills of elementary school children? Findings from a randomized experiment

BACKGROUND

Coding has been added to school curricula in several countries, being one of the necessary competencies of the 21st century. Although it has also been suggested to foster the development of several cognitive skills such as computational thinking and problem-solving, studies on the effects of coding are very limited, provide mixed results, and lack causal evidence.

AIM

This study aims to evaluate the impact of a learn-to-code programme on three cognitive skills in children: computational thinking, fluid intelligence, and spatial orientation, using a randomized trial.

SAMPLE

One hundred seventy-four (n = 81 girls) 4th-grade children participated in the study.

METHODS

Children were randomly assigned to one of the three 10-week learning programmes: learn-to-code (treatment of interest), mathematics (another STEM-related comparison treatment), and reading (control). Children responded to paper-pencil computational thinking, and spatial orientation measurements, and face-to-face matrix reasoning task at pre- and post-tests.

RESULTS

Results showed that children's computational thinking scores increased significantly only in the learn-to-code condition. Fluid intelligence significantly increased in all conditions, possibly due to a practice effect. The spatial orientation did not improve in any of the conditions.

CONCLUSION

These findings suggested that learning to code can be selectively beneficial for the development of computational thinking skills while not effective for spatial reasoning and fluid intelligence.

Exploring Computational Thinking Skills Training Through Augmented Reality and AIoT Learning

Given the widespread acceptance of computational thinking (CT) in educational systems around the world, primary and higher education has begun thinking about how to cultivate students' CT competences. The artificial intelligence of things (AIoT) combines artificial intelligence (AI) and the Internet of things (IoT) and involves integrating sensing technologies at the lowest level with relevant algorithms in order to solve real-world problems. Thus, it has now become a popular technological application for CT training. In this study, a novel AIoT learning with Augmented Reality (AR) technology was proposed and explored the effect of CT skills. The students used AR applications to understand AIoT applications in practice, attempted the placement of different AR sensors in actual scenarios, and further generalized and designed algorithms. Based on the results of the experimental course, we explored the influence of prior knowledge and usage intention on students' CT competence training. The results show that proposed AIoT learning can increase students' learning intention and that they had a positive impact on problem solving and comprehension with AR technology, as well as application planning and design.

Computational Thinking and STEM in Agriculture Vocational Training: A Case Study in a Greek Vocational Education Institution

Due to the dynamic nature of the agricultural industry, educators and their institutions face difficult challenges as they try to keep pace with future demands for knowledge and skilled workers. On the other hand, computational thinking (CT) has drawn increasing attention in the field of science, technology, engineering, and mathematics (STEM) education at present and, as advanced technologies and tools emerge, it is imperative for such innovations to be sustained with knowledge and skill among STEM educators and practitioners. The present case study aims to explore the relation between CT, STEM and agricultural education training (AET) in a Greek vocational training institute (IEK), the Agriculture IEK of Metamorfosis city (IEKMC), which is active in agriculture education. The research methodology is utilized according the positivist philosophical approach through data acquisition employing a questionnaire and the quantitative (statistical) analysis of data collected. The sample consists of IEKMC educators and students selected based on simple random sampling. Based on the participants belief that CT and STEM philosophy add value in the learning process, it focuses on the application of knowledge in the real world (students) and problem solving using new technologies (educators). Educators consider "experiments" as the most significant educational tool for problem solving in teaching practice. Students rate Greek Agriculture Education and Training (GAET) higher than educators. However, the participants evaluate GAET very low due to the lack of new innovative teaching methods being introduced. Finally, there is great interest in the implementation of CT and STEM in the European Union (EU) by students and educators.

A Novel Real-Time MATLAB/Simulink/LEGO EV3 Platform for Academic Use in Robotics and Computer Science

Over the last years, mobile robot platforms are having a key role in education worldwide. Among others, LEGO Robots and MATLAB/Simulink are being used mainly in universities to improve the teaching experience. Most LEGO systems used in the literature are based on NXT, as the EV3 version is relatively recent. In contrast to the previous versions, the EV3 allows the development of real-time applications for teaching a wide variety of subjects as well as conducting research experiments. The goal of the research presented in this paper was to develop and validate a novel real-time educational platform based on the MATLAB/Simulink package and the LEGO EV3 brick for academic use in the fields of robotics and computer science. The proposed framework is tested here in different university teaching situations and several case studies are presented in the form of interactive projects developed by students. Without loss of generality, the platform is used for testing different robot path planning algorithms. Classical algorithms like rapidly-exploring random trees or artificial potential fields, developed by robotics researchers, are tested by bachelor students, since the code is freely available on the Internet. Furthermore, recent path planning algorithms developed by the authors are also tested in the platform with the aim of detecting the limits of its applicability. The restrictions and advantages of the proposed platform are discussed in order to enlighten future educational applications.

Research on Head-Mounted Virtual Reality and Computational Thinking Experiments to Improve the Learning Effect of AIoT Maker Course: Case of Earthquake Relief Scenes

In this study, the head-mounted virtual reality (VR) technology is adpoted for computational thinking teaching in the AIoT Maker course teaching. The earthquake relief situation is designed in the VR in the course scenario, because in the context of situational thinking, pre-emptive training in the face of emergency disasters has been conducted through observation meetings or training courses. Through listening to lecturers or experienced personnel to share experiences, students often have a harder time thinking about real scenes and it is harder to think creatively how to design with the emergency disaster response. In view of this, this research will combine the development and evaluation of earthquake relief training courses for head-mounted VR and computational thinking experiments to explore the use of VR and computational thinking experiments to drive students to create ideas for real disaster relief scenarios. Through computational thinking, students think about different script situations and discuss in each scene to find a suitable maker design of the AIoT project. Finally, this study combined with its modular space program training to develop students' programming skills. According to the experiment, this study is able to strength students' practical learning motivation, and follow-up employ ability training for course learning.

Coding in Primary Grades Boosts Children's Executive Functions

Several programs have been developed worldwide to improve children’s executive functions (EFs). Yet, the role played in EF development by learning activities embedded in the school curriculum has received scarce attention. With two studies, we recently tested the effects of computational thinking (CT) and coding—a new element of the primary school curriculum—on the development of children’s EFs. CT stimulates the ability to define a clear and orderly sequence of simple and well-specified steps to solve a complex problem. We conjecture that CT skills are associated to such EF processes as response inhibition and planning. In a first between-group cluster-randomized controlled trial, we tested the effects of 1-month coding activities on 76 first graders’ planning and response inhibition against those of 1-month standard STEM activities of a control group. In a second study, we tested the effects of 1-month coding activities of 17 second graders in two ways: within group (longitudinally), against 7 months of standard activities experienced by the same children (experimental group); and between groups, in comparison to the effects of standard STEM activities in a control group of 19 second graders. The results of the two studies show significant benefits of learning to code: children exposed to coding improved significantly more in planning and inhibition tasks than control children did. The longitudinal data showed that improvements in planning and inhibition skills after 1 month of coding activities (eight lessons) were equivalent to or greater than the improvement attained after 7 months of standard activities. These findings support the hypothesis that learning CT via coding can significantly boost children’s spontaneous development of EFs.

Sentinel plants as programmable processing units: insights from a multidisciplinary perspective about stress memory and plant signaling and their relevance at community level

Stress memory and an effective signaling among individuals in a given community are recognized to improve plant performance under recurrent stressful conditions. As living beings with memory and signaling abilities, plants can be considered as processing units and then be trained - or programmable from a computational viewpoint - and prepared for facing biotic and abiotic stresses. Here, we propose that sentinel plants could improve the resilience of agricultural and natural communities by reducing the impact of biotic or abiotic stressors on their neighbors. Modeling plants as programmable (or trainable) processing units compels us to think about a multidisciplinary perspective for integrating stress memory, signaling, and resilience of biological systems into executable programs, fostering the creation of applications and technologies that would benefit from the spatiotemporal dynamics related to plant-plant and plant-environment interactions.

Computational thinking and thinking about computing

Computational thinking will influence everyone in every field of endeavour. This vision poses a new educational challenge for our society, especially for our children. In thinking about computing, we need to be attuned to the three drivers of our field: science, technology and society. Accelerating technological advances and monumental societal demands force us to revisit the most basic scientific questions of computing.