ArticlePublisher preview available

Designing for discovery learning of complexity principles of congestion by driving together in the TrafficJams simulation

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

Abstract and Figures

We propose and evaluate a framework supporting collaborative discovery learning of complex systems. The framework blends five design principles: (1) individual action: amidst (2) social interactions; challenged with (3) multiple tasks; set in a (4) a constrained interactive learning environment that draws attention to (5) highlighted target relations. The framework addresses a persistent tension in discovery-based pedagogy between offering students the freedom to initiate, experiment, and explore and providing them with tailored experiences with many instances of particular relations underlying the target conceptual structure. The framework was realized with TrafficJams, a participatory simulation in which students drive together. A class of high-school students worked with TrafficJams over 2.5 h. The teacher’s role was to orchestrate the activity but there was no explicit instruction of the traffic and complexity principles. The students completed pre- and post-test questionnaires and their activities were observed and logged. In terms of driving in the simulation, the students learned to drive in ways that reduced congestion in traffic by decreasing lane and speed changes, and keeping their speed down. Even though there was no explicit teaching, half of the students learned that car speed distribution alone can generate traffic jams with no additional causes; and, keeping a safe following distance from the next driver increases everyone’s speed. Our study suggests that the learning environment partially met both the overarching design goal of constrained discovery and the specific content goal of systems reasoning.
This content is subject to copyright. Terms and conditions apply.
Designing for discovery learning of complexity principles
of congestion by driving together in the TrafficJams
simulation
Sharona T. Levy
1
Ran Peleg
1
Eyal Ofeck
1
Naamit Tabor
1
Ilana Dubovi
1
Shiri Bluestein
1
Hadar Ben-Zur
1
Received: 13 March 2017 / Accepted: 4 December 2017 / Published online: 31 January 2018
Springer Science+Business Media B.V., part of Springer Nature 2018
Abstract We propose and evaluate a framework supporting collaborative discovery
learning of complex systems. The framework blends five design principles: (1) individual
action: amidst (2) social interactions; challenged with (3) multiple tasks; set in a (4) a
constrained interactive learning environment that draws attention to (5) highlighted target
relations. The framework addresses a persistent tension in discovery-based pedagogy
between offering students the freedom to initiate, experiment, and explore and provid-
ing them with tailored experiences with many instances of particular relations underlying
the target conceptual structure. The framework was realized with TrafficJams, a partici-
patory simulation in which students drive together. A class of high-school students worked
with TrafficJams over 2.5 h. The teacher’s role was to orchestrate the activity but there was
no explicit instruction of the traffic and complexity principles. The students completed pre-
and post-test questionnaires and their activities were observed and logged. In terms of
driving in the simulation, the students learned to drive in ways that reduced congestion in
traffic by decreasing lane and speed changes, and keeping their speed down. Even though
there was no explicit teaching, half of the students learned that car speed distribution alone
can generate traffic jams with no additional causes; and, keeping a safe following distance
from the next driver increases everyone’s speed. Our study suggests that the learning
environment partially met both the overarching design goal of constrained discovery and
the specific content goal of systems reasoning.
Keywords Complex systems Design Human factors Simulations Traffic
&Sharona T. Levy
stlevy@edu.haifa.ac.il
1
Faculty of Education, University of Haifa, 199 Aba Khoushy Avenue, Mount Carmel,
3498838 Haifa, Israel
123
Instr Sci (2018) 46:105–132
https://doi.org/10.1007/s11251-017-9440-2
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... Computer simulations designed to teach driving principles normally focus on experiences that promote elementary driving knowledge such as accelerating, decelerating or steering: that is, the main actions and reactions of a driver in a driving environment (Pollatsek et al., 2011;Schiff et al., 1994). Simulation environments are also effective in showing new or unusual traffic environments or circumstances, and in learning and training new driving behaviors (Arslanyilmaz and Sullins, 2019;Beloufa et al., 2019;Blissing et al., 2019;Cavallo et al., 2019) some related to congested flows (Levy et al., 2018). ...
... To achieve these goals, some ordinary elements and circumstances (e.g., rearview mirror, presence of traffic lights, passing road sections with different speed limits) have been implemented in the DI simulator, as well as some very unusual or impossible ones (e.g., adopting bird's-eye views from different angles and positions over the whole platoon at will, displaying traffic lights on each single car, connecting cars with springs, activating radar-like displays). Like other recent attempts to model and understand complex systems (Levy et al., 2018), the DI simulator leverages uncommon paths or perspectives to frame participants' analysis and comprehension of CF at large. The DI course includes three modules (Fig. 3): Knowing the controls (Module A); Teaching DI (Modules B-D); and Evaluation (Module E). ...
... In addition, the measures of emotions and eye-tracking (Lucas-Alba et al., 2020), not included in the present study, can shed light on the perceptual and cognitive-emotional processes during pre-and post-test with a standard driving simulator, but also during the actual learning phases of the DI course. It is also a pending improvement to incorporate more complex scenarios into the DI course, including overtaking, lane changes or exits and entries (see Levy et al., 2018) from the driver's perspective. Finally, analyzing the slight decrease for average speed and possibly improving the second tutorial also seems like an important future goal. ...
Article
Full-text available
Background For many decades, car-following (CF) and congestion models have assumed a basic invariance: drivers’ default driving strategy is to keep the safety distance. The present study questions that Driving to keep Distance (DD) is a traffic invariance and, therefore, that the difference between the time required to accelerate versus decelerate must necessarily determine the observed patterns of traffic oscillations. Previous studies have shown that drivers can adopt alternative CF strategies like Driving to keep Inertia (DI) by following basic instructions. The present work aims to test the effectiveness of a DI course that integrates 4 tutorials and 4 practice sessions in a standard PC computer designed to learn more adaptive driving behaviors in dense traffic. Methods. Sixty-eight drivers were invited to follow a leading car that varied its speed on a driving simulator, then they took a DI course on a PC computer, and finally they followed a fluctuating leader again on the driving simulator. The study adopted a pretest-intervention-posttest design with a control group. The experimental group took the full DI course (tutorials and then simulator practice). The control group had access to the DI simulator but not to the tutorials. Results. All participating drivers adopted DD as the default CF mode on the pre-test, yielding very similar results. But after taking the full DI course, the experimental group showed significantly less accelerations, decelerations, and speed variability than the control group, and required greater CF distance, that was dynamically adjusted, spending less fuel in the post-test. A group of 8 virtual cars adopting DD required less space on the road to follow the drivers that took the DI course.
... A statistically significant correlation was found between articles mentioning digitalisation and articles mentioning modelling. As known from the literature, studies that focus on developing teachers' or students' modelling competence often integrate digital modelling tools and software (e.g., Levy et al., 2018;Rachmatullah & Wiebe, 2022), which can explain this finding. ...
... Number of publications per year, separated by the type of empirical study: intervention (Int) or diagnostic (Dia)Table 5Frequencies of system attributes in our sample (n = 255) and example articles (articles may include more than one system attributeCohen, 2018;Espinoza et al., 2022;Hmelo-Silver et al., 2000;Levy et al., 2018; Peppler et al.Number of publications per year, separated by system attributes of complexity/complex system (Cpx), interactions/relationships (Int), components (Cmp), phenomena (Phe) and dynamics/equilibrium (Dyn) ...
Article
Full-text available
Understanding complex systems is important in science and has become a prominent aspect of STEM education in recent years. System thinking plays a critical role, focusing on system attributes such as interactions between components, emerging phenomena and hierarchical organisation. In this study, we provide a network analysis of bibliometric information and a research synthesis of empirical studies on system thinking and complexity in STEM education from the past two decades, aiming to identify trends in the field. We reviewed 255 empirical published studies identified from Web of Science database and found a sharp increase in the number of studies on system thinking after 2016. In the research synthesis, we categorised these studies under five categories: (i) study population, (ii) disciplinary field, (iii) empirical study type, (iv) system attributes and (v) cognitive aspects. In the results, we found that most studies focused on higher education (86 papers) and biology (67 papers), while only few of the studies focused on pre- and in-service teachers (14 and 23 papers, respectively) as well as on elementatry students (22 papers). Complexity and interactions emerged as the most mentioned system attributes (89 and 55 papers, respectively), while thinking and understanding were the most mentioned cognitive aspects (112 and 73 papers, respectively). In addition, an increasing focus on digitalisation (68 papers) and modelling (61 papers) was identified. We discuss these emerging trends and identify research gaps and directions for future studies.
... Simulation environments are also effective in showing new or unusual traffic environments or circumstances, and in learning and training new driving behaviors [40], [41], [42], [43]. One learning environment that attends to driving in emergent traffic and congestion is TrafficJams [44], in which a group of people drive their cars together on a single simulated road. Unlike the WDC, this learning environment attends not specifically to the DD and DI CF strategies but to other issues of keeping a safe distance (with a specific strategy), braking and accelerating and shifting between lanes. ...
... To achieve these goals, some ordinary elements and circumstances (e.g., rearview mirror, presence of traffic lights, passing road sections with different speed limits) have been implemented in the WDC, as well as some very unusual or impossible ones (e.g., adopting bird's-eye views from different angles and positions over the whole platoon at will, displaying traffic lights on each single car, connecting cars with springs, activating radar-like displays). Like other recent attempts to model and understand complex systems [44], the WDC leverages uncommon paths or perspectives to frame participants' analysis and comprehension of CF at large. ...
Article
Full-text available
This paper addresses the problem of traffic congestion through a learning perspective, highlighting the capabilities of Information and Communication Technologies to transform society. Recent physical and mathematical analysis of congestion reveals that training drivers to keep a safe distance systematically contributes to the emergence and maintenance of interference congestion (so-called phantom traffic jam). This paper presents the WaveDriving Course (WDC), a simulated learning environment designed to help drivers progress from the traditional Drive-to-keep-Distance (DD) technique to a new car-following (CF) principle better suited for wave-like traffic, Drive-to-keep-Inertia (DI). The WDC is based on the ordinary knowledge of the driver (e.g., going through a series of traffic lights), and presents this situation in terms of two possible simultaneous behavioral strategies. The driver has the opportunity to verify that it is possible to achieve the same objective with different consequences. Finally, the WDC checks to what extent this learning generates transfer patterns in the analogous case of CF. The paper focuses on results concerning the first WDC module: the traffic-light analogy. Forty-two participants followed the whole learning procedure for about 30 min. An evaluative CF test was administered before and after visioning the tutorial and practicing on the simulator. Overall, transference from this traffic-light analog to the CF situation (posttest) was successful. Results confirm the adoption of the expected DI strategies (speed variability decreased, distance and distance variability to leader increased, fuel consumption decreased, platoon elongation decreased etc.). The need to improve the WDC teaching of the appropriate CF distance is discussed.
... Pengetahuan awal dan aktivitas yang dilakukan oleh siswa dalam discovery learning menentukan pengetahuan baru/pemahaman yang diperoleh, sebagaimana Bakker (2018) yang lebih menggambarkan belajar dengan discovery learning lebih seperti sekumpulan orang buta (pengetahuan terbatas) yang memegang bagian tubuh gajah (aktivitas) akan memiliki persepsi sesuai bagian yang dipegang bukan kesatuan utuh. Oleh karenanya pengajaran dan teknologi yang tepat dapat membantu apa yang dilihat (diketahui) siswa sehingga mereka dapat menemukan wawasan tertentu (Chase and Abrahamson, 2018;Levy et al., 2018;Wilkerson et al., 2018). ...
Article
Full-text available
Student learning outcomes in learning in class VIII SMP Muhammadiyah 9 Yogyakarta is still low. Factors causing low learning outcomes include not using any learning model and still being teacher-centered. This study aimed to determine the effect of Discovery learning learning models on student learning outcomes in the digestive system material class VIII at SMP Muhammadiyah 9 Yogyakarta. This type of research is a quasi-experiment. This study's population were all VIII grade students of SMP Muhammadiyah 9 Yogyakarta consisting of five classes, namely classes A, B, C, D, and E, with 140 students. In this study, purposive sampling was conducted based on certain considerations so that 2 class samples were obtained, namely class VIII C as the control class and VIII E as the experimental class. Data collection techniques with tests. Data collection instruments were in the form of pretest and posttest questions. The analysis technique used is descriptive quantitative. Research Results Learning outcomes were analyzed by t-test statistics at the level of significance 5% obtained t-count 0.302 and t-table = 2.01063, so t-count < t-table. Therefore, the Discovery learning model does not affect the learning outcomes of VIII grade students of SMP Muhammadiyah 9 Yogyakarta.
... In contrast, typical high-fidelity commercial driving simulators (fixed-base) usually cost around $10,000 to $100,000. With its highly affordable price, this driving simulator can be a popular choice not only for academic research purposes, but also for conducting driving classes 19 (b) A $30000 driving simulator setup that used three mounted projectors and three projector screens with a dimension of 223 ...
... In the comparison class, students conduct simulated experimental tasks, which are explored explicitly in the classroom and the Edmodo. Several studies have shown that the use of virtual laboratories could support discovery learning (Levy et al., 2018). Karlsson et al. (2013) stated, however, that this kind of learning environment should be able to provide additional tools that can connect student learning experiences with relevant phenomena. ...
Article
Full-text available
This study aims to investigate the effect of Science, Technology, Engineering, and Mathematics-Project Based Learning (STEM-PjBL) and discovery learning on students' problem-solving abilities. The research is a Quasi-Experiment with a Nonequivalent Pretest-Posttest Control Group Design. The participants involved are 53 students of class X from a high school in Malang, where 28 students studied with STEM-PjBL, and 25 students studied with discovery learning. This research was conducted on the subject of impulse and momentum. In this analysis, researchers have developed problem-solving tools with a particular field approach to impulse and momentum topics in order to obtain an instrument with a reliability of 0.81. This instrument collects student problem-solving data before and after learning both in the experimental class and in the comparison class. Problem-solving skills data were analyzed using descriptive statistics and inferential statistics. The results showed a significant difference in the scores of students' problem-solving abilities in the experimental class and the comparison class (p<0.05). The problem-solving ability in the experimental class (Md=78.74) was higher than the comparison class (Md=70.00). In STEM-PjBL learning, students are better trained and challenged to solve problems in everyday life. Compared to the comparison class, learning in the experimental class is more able to accommodate students' ideas and make students more interested in learning. In conclusion, STEM-PjBL has a significant positive effect on improving students' problem-solving abilities rather than discovery learning.
... Using a flexible, improvisational approach can support teachers in finding a balance between their plans and student agency, which is key to effective and engaging instruction (Duschl & Wright, 1989), and perhaps especially beneficial when teaching higherorder concepts such as complex systems (Levy et al., 2018). Connecting improvisation with teaching is not a new idea (Berliner, 1987;Eisner, 2002;Erickson, 1982;Halverson, 2018;Lampert & Graziani, 2009;Leinhardt & Greeno, 1986;Sawyer, 2004a, b;Sawyer, 2011;Yinger, 1987) as scholars have argued that improvisation can be a model for balancing the structure and flexibility that instruction requires (Beghetto & Kaufman, 2011;Berliner, 2004;Sawyer, 2004a;Sawyer, 2011). ...
Article
Full-text available
In inquiry-based science lessons teachers face the challenge of adhering to curricular goals while simultaneously following students’ intuitive understandings. Improvisation (improv) provides a useful frame for understanding teaching in these inquiry-based contexts. This paper builds from prior work that uses improv as a metaphor for teaching to present a translated model for analysis of teaching in an inquiry-based, elementary school science lesson context. We call our model instructional improv, which shows how a teacher spontaneously synthesizes rules of improv with teaching practices to support student learning, engagement, and agency. We illustrate instructional improv through case study analysis of video recorded classroom interactions with one teacher and 26 first and second grade students learning about the complex system of honey bee pollination in a mixed reality environment. Our model includes the following defining features to describe how teaching happens in this context: the teacher 1) tells a story ; 2) reframes mistakes as opportunities ; 3) agrees ; 4) yes ands ; 5) makes statements (or asks questions that elicit statements) ; and 6) puts the needs of the classroom ensemble over individuals . Overall, we show how instructional improv helps explain how teachers can support science discourse and collective storytelling as a teacher (a) shifts power and agency to students; (b) balances learning and agency; and (c) makes purposeful instructional decisions. Findings have immediate implications for researchers analyzing interactions in inquiry-based learning environments and potential future implications for teachers to support inquiry learning.
... In contrast, typical high-fidelity commercial driving simulators (fixed-base) usually cost around $10,000 to $100,000. With its highly affordable price, this driving simulator can be a popular choice not only for academic research purposes, but also for conducting driving classes 19 (b) A $30000 driving simulator setup that used three mounted projectors and three projector screens with a dimension of 223 ...
Article
Collision warning system plays a key role in the prevention of driving distractions and drowsy driving. Previous studies have proven the advantages of tactile warnings in reducing driver’s brake response time. At the same time, tactile warnings have been proved effective in take-over request (TOR) for partially autonomous vehicles. How the performance of tactile warnings can be optimized is an ongoing hot research topic in this field. Thus, the presented low-cost driving simulation software and methods are introduced to attract more researchers to take part in the investigation. The presented protocol has been divided into five sections: 1) participants, 2) driving simulation software configuration, 3) driving simulator preparation, 4) vibrating toolkit configuration and preparation, and 5) conducting the experiment. In the exemplar study, participants wore the tactile vibrating toolkit and performed an established car-following task using the customized driving simulation software. The front vehicle braked intermittently, and vibrating warnings were delivered whenever the front vehicle was braking. Participants were instructed to respond as quickly as possible to the sudden brakes of the front vehicle. Driving dynamics, such as the brake response time and brake response rate, were recorded by the simulation software for data analysis. The presented protocol offers insight into the exploration of the effectiveness of tactile warnings on different body locations. In addition to the car-following task that is demonstrated in the exemplar experiment, this protocol also provides options to apply other paradigms to the driving simulation studies by making simple software configuration without any code development. However, it is important to note that due to its affordable price, the driving simulation software and hardware introduced here may not be able to fully compete with other high-fidelity commercial driving simulators. Nevertheless, this protocol can act as an affordable and user-friendly alternative to the general high-fidelity commercial driving simulators.
Article
The purpose of this qualitative descriptive case study was to examine teachers’ perspectives and review preparation materials to understand why students in SS3 were not proficient on the mathematics SSCE standardized assessments. Teachers were randomly selected, and semistructured phone interviews using open-ended questions were utilized to understand teacher perspectives, course preparation materials, and how the materials could be improved. The study aimed to determine what teachers perceive to be working, what challenges exist, and describe the mathematics preparation materials used in preparing students for the mathematics SSCE standardized assessments. The study revealed the need to develop the senior secondary schedule to make improvements in curriculum implementation and a need for appropriate instructional materials and adequate instructional time to ensure essential learning outcomes and core skills are taught effectively.
Article
Full-text available
This book contributes to the current debate about how to think and talk about human thinking so as to resolve or bypass such time-honored quandaries as the controversy of nature vs. nurture, the body and mind problem, the question of learning transfer, and the conundrum of human consciousness. The author responds to the challenge by introducing her own “commognitive” conceptualization of human thinking. She argues for this special approach with the help of examples of mathematical thinking. Except for its contribution to theorizing on human development, the book is relevant to researchers looking for methodological innovations, and to mathematics educators seeking pedagogical insights and improvements.
Article
Full-text available
Many innovative approaches to education such as problem-based learning (PBL) and inquiry learning (IL) situate learning in problem-solving or investigations of complex phenomena. Kirschner, Sweller, and Clark (2006)45. Kirschner , P. A. , Sweller , J. and Clark , R. E. 2006. Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist., 41: 75–86. [Taylor & Francis Online], [Web of Science ®]View all references grouped these approaches together with unguided discovery learning. However, the problem with their line of argument is that IL and PBL approaches are highly scaffolded. In this article, we first demonstrate that Kirschner et al. have mistakenly conflated PBL and IL with discovery learning. We then present evidence demonstrating that PBL and IL are powerful and effective models of learning. Far from being contrary to many of the principles of guided learning that Kirschner et al. discussed, both PBL and IL employ scaffolding extensively thereby reducing the cognitive load and allowing students to learn in complex domains. Moreover, these approaches to learning address important goals of education that include content knowledge, epistemic practices, and soft skills such as collaboration and self-directed learning.
Article
Full-text available
Evidence for the superiority of guided instruction is explained in the context of our knowledge of human cognitive architecture, expert–novice differences, and cognitive load. Although unguided or minimally guided instructional approaches are very popular and intuitively appealing, the point is made that these approaches ignore both the structures that constitute human cognitive architecture and evidence from empirical studies over the past half-century that consistently indicate that minimally guided instruction is less effective and less efficient than instructional approaches that place a strong emphasis on guidance of the student learning process. The advantage of guidance begins to recede only when learners have sufficiently high prior knowledge to provide “internal” guidance. Recent developments in instructional research and instructional design models that support guidance during instruction are briefly described.
Article
The study explores how a complexity approach empowers science learning. A complexity approach represents systems as many interacting entities. The construct of micro–macro compatibility is introduced, the degree of similarity between behaviors at the micro- and macro-levels of the system. Seventh-grade students’ learning about gases was studied using questionnaires and interviews. An experimental group (n = 47) learned with a complexity curriculum that included agent-based computer models, a workbook, class discussions, and laboratory experiments. A comparison group (n = 45) learned with a normative curriculum, incorporating lectures, a textbook, class discussions, and laboratory experiments. Significant learning gains and strong effect sizes were found in the experimental group's overall learning. Diffusion, density, and kinetic molecular theory were learned better with a complexity approach. Pressure, temperature, and the gas laws were learned similarly with both approaches. Learning to notice micro-level behaviors and their probabilistic nature was greater with the complexity approach. Analysis showed that only concepts that have less “micro–macro compatibility” were learned better with a complexity approach. Thus, a complexity approach helps separate the microbehaviors and then relate them to the macrobehaviors when these behaviors are dissimilar. We discuss how micro–macro compatibility helps point to concepts whose learning would benefit strongly from a complexity approach.
Article
There is a growing interest in role-playing activities, both in school classrooms and in the culture at large. Despite this growing interest, role-playing activities are rare in mathematics and science classrooms. In social-studies activities, a major goal is to help students adopt the perspective of another person. However, mathematics and science classes typically discourage this type of perspective-taking; science is usually taught as a process of detached observation and analysis of phenomena, not active participation within phenomena. In this article, we argue that role-playing activities can play a powerful role in mathematics and science education - particularly in the study of the new sciences of complexity. We present detailed descriptions and analyses of 2 role-playing activities that we have organized. Each activity is designed to help students explore (in a very participatory way) the behaviors of complex systems, helping them develop better intuitions on how complex phenomena can arise from simple interactions, and predictable patterns from random events.