In this Work-in-Progress Research Paper, we explore students' emotions and motivations in a game-based learning (GBL) environment. GBL has been shown to be effective in improving students' cognitive and non-cognitive learning outcomes, including emotions and motivations. In this study, we focus on the Cone Penetration Testing module of GeoExplorer's virtual learning environment, which has been shown to enable civil engineering undergraduates to develop key competencies necessary to problem-solve and make critical on-site decisions. This paper examines the impacts of GeoExplorer on students' emotions and motivations by asking: (1) How, if at all, do students' self-reported emotions shift through experiencing Geo-Explorer, and how does GeoExplorer contribute to these shifts, if at all? and (2) What is the connection between students' self-reported emotions and their self-reported motivational attitudes, both before and after they engage with GeoExplorer? Responses from 60 participants about their emotions and motivations pre-and post-engagement with GeoExplorer were analyzed. Inductive methods, including open coding and the constant comparative approach, were used to analyze the following emotions-based survey item: Thinking about your experience over the past week in the course, what particular emotions and/or thoughts about the course both inside and outside the classroom stand out for you? Deductive analytical practices, including closed coding, were used to analyze the following motivations-based survey item: What factors contributed to your motivation over the past week in the course? Consistent with literature, our preliminary findings indicate an interrelationship between GBL experiences and shifts in students' reported emotions. We also determine a link between these emotional shifts and motivational changes from pre- to post-engagement with GeoExplorer. It is the interplay of these three elements - GBL experience, student emotions, and student motivations - that is at the center of this work.

This Work-in-Progress Research Paper centers on game-based learning and its impact on student motivation as a function of their self-defined demographic factors. Specifically, this work investigates the game-based learning experience of civil engineering undergraduates engaged with the Cone Penetration Testing module of GeoExplorer, a virtual learning environment that simulates in-field learning about the structural properties of soil, providing students with the opportunity to practice competencies and mindsets associated with real-world data collection and analyses. In this paper, we explore the impacts of GeoExplorer on student motivation by addressing the following research questions: (1) How, if at all, do students experience identifiable motivational shifts over the course of their engagement with GeoExplorer? (2) What is the interplay between engagement with GeoExplorer, demographic factors, including students' racial, ethnic, and gender identities, and student motivation? and (3) How can game-based learning environments best address the needs of students with different motivational attitudes? Preliminary analyses of 60 response pairs to the pre- and the post-GeoExplorer engagement surveys from 2021 were analyzed. Deductive analytical practices using ‘a priori’ qualitative coding, based on Self-Determination Theory (SDT) of motivation, were used to examine the following survey item: What factors contributed to your motivation over the past week in the course? Please give specific examples of activities, interactions, emotions, thoughts, etc. that may have contributed to your motivation. While our early findings indicate distinct differences in students' motivational outcomes between the pre- and post-survey, no clear patterns in motivational shifts are identified across the board, suggesting that the GeoExplorer experience may have impacted each student's motivation uniquely. However, patterns emerged between students' pre-survey motivation types, based on demographic factors. Additionally, unique shifts in motivational attitudes between the pre- and post-surveys were found to occur within each demographic grouping. These findings and challenges in performing this study are further discussed with a proposal for possible future directions.

This Work-in-Progress research paper focuses on the game-based learning environment of GeoExplorer, a digital learning tool that simulates Cone Penetration Testing (CPT) – a field test that civil engineers conduct to understand soil properties. This paper aims to investigate the gendered patterns of student interaction with GeoExplorer, if any, and the associated gendered patterns of content comprehension and self-efficacy related to one's ability to pursue CPT in the field, if any. As such, we ask: (1) How, if at all, does gender affect a student's belief in their ability to apply skills gained through engagement with GeoExplorer in real world environments? and (2) How, if at all, do prior gaming experience and gender impact the GeoExplorer play experience? Four open-ended semi-structured interviews regarding students' experience with gameplay, gender identity, and learning were analyzed. Preliminary analyses used narrative and grounded theory approaches. Our early findings indicate a lack of student insight on the role of their gender identity on their gameplay experience and the presence of a gendered impact of gameplay on student learning and self-efficacy in carrying out CPT in the field.

Geotechnical engineers work with a complex material. Unlike steel or concrete, soil is heterogeneous, and its properties are difficult to predict. As such, judgment plays a significant role in geotechnical engineering practice and the design process is unavoidably iterative. This WIP starts with geotechnical engineering as the origin for defining engineering judgment, but the emerging theory can service all engineering decision making. The process through which aspiring engineers practice engineering judgment in their education remains a research area in its adolescence. Members of industry posit that experience is essential for competent engineering practice, but traditional engineering education practices provide few opportunities to acquire such experience. The GeoExplorer project is a mixed reality "mock internship" that allows students to get preliminary experience with field testing through a mixed-reality game-based learning environment. The CPT module of GeoExplorer was designed to both develop and measure gains in engineering judgment. The importance of defining engineering judgment with respect to engineering education standards became clear when designing this module to serve undergraduate engineering classrooms.

This Work-in-Progress Research paper focuses on digital game-based learning (DGBL), which refers to the use of a virtual environment to support students’ learning. In this exploratory study, we examine how students engage with GeoExplorer, a digital game-based learning environment that simulates Cone-Penetration Testing (CPT), an on-site test used in geotechnical engineering to investigate soil properties that students typically don’t have access to. In GeoExplorer’s CPT activity, students participate in a virtual internship in which they examine several sites with varied types of soil. This paper investigates DGBL environments by leveraging Self-Determination Theory (SDT) to ask the following research questions: (1) How do "freedom" and autonomy within GeoExplorer encourage students’ new emergent learning strategies? and (2) How do emergent learning strategies in GeoExplorer support students’ confidence as they self-guide their learning? Ten open-ended semi-structured interviews were performed with civil engineering students from three U.S.-based institutions. The data are analyzed using narrative analysis and a grounded theory approach. Our preliminary findings indicate that, while GeoExplorer is intended as a complement to in-person learning, it serves both as a complement and supplement to the online learning that helps to engage students during the pandemic. Students share that a felt sense of "freedom" within GeoExplorer encourages them to engage in different emergent learning strategies, such as repetition and trial and error. Students also describe that these emergent learning strategies promote knowledge retention and understanding, and further support their confidence in performing CPT. Our preliminary findings provide opportunities for students to practice autonomy and develop competency – two out of three basic psychological needs in SDT – in their educational processes.

This Work-in-Progress paper focuses on the qualitative aspects of a larger mixed-methods study about GeoExplorer, a game-based learning aspect of a mixed reality educational environment where students participate in a mock internship with the goal to complete a geotechnical mission involving Cone Penetration Testing, a civil engineering field technique students traditionally get very little exposure to due to its complexity and cost. This work seeks to understand how mixed reality learning environments, specifically game-based learning, support (i) creation of individualized hands-on learning opportunities, particularly during the pandemic-driven remote learning paradigm, and (ii) students' development along various noncognitive axes - confidence and motivation. Methods of narrative analyses and grounded theory are used to identify emergent themes in interviews with 10 undergraduate civil engineering students who experienced GeoExplorer in their required geotechnical engineering courses. Our preliminary findings indicate that the GeoExplorer activity was perceived by students as a novel learning experience, particularly welcomed in a time of remote learning, that motivates them to engage more with content and creates individualized hands-on experiences. Students describe how the activity affects their perceived confidence, often gendered, regarding their ability to perform civil engineering fieldwork. Further analyses of these findings may shed light on the ways in which mixed reality learning environments support equitable learning opportunities for all students.

Game-based learning has long been heralded as a promise to transform education into a more engaging and experiential paradigm. Its implementation in engineering education has thus far shown that promise, yet more evidence is needed for widespread adoption. Our work focuses on issues of equity, inclusivity, and diversity, thus surfacing the question of whether game-based learning benefits each and every student. To date, these issues have not received much attention in game-based learning educational research landscape, despite its poignancy, given today's global social climate and the systematic lack of equity and diversity in engineering education. With a focus on gender and race/ethnicity we reflect on the outcomes of implementing game-based learning environment in undergraduate geotechnical engineering courses (n = 362). We find evidence that game-based learning supports positive outcomes and provides an equitable learning environment. However, we also note several challenges that are further discussed.

The first-generation time-series synthetic aperture radar interferometry (TSInSAR) technique persistent-scatterer (PS) InSAR has been proven effective in ground deformation measurement over areas with high reflectivity by taking advantage of coregistered temporally coherent pointwise scatterers. In order to increase the spatial density of measurement points and quality of displacement time series over moderate reflectivity scenes, a second-generation TSInSAR called SqueeSAR was developed to extract displacement information from both PSs and distributed scatterers, by taking into account their temporal coherence and their spatial statistical behavior. In this paper, we propose a new second-generation TSInSAR, which is referred to as joint-scatterer (JS) InSAR, to measure the line-of-sight surface displacement using the neighboring pixel stacks. A novel goodness-of-fit testing approach is proposed to analyze the similarity between two JS vectors based on time-series likelihood ratios. By taking advantage of the proposed test, a new spatially adaptive filter is developed to estimate the covariance matrix. Based on the estimated covariance matrix, the projection of the joint signal subspace onto the corresponding joint noise subspace is applied to retrieve phase history. With coherence information of neighboring pixel stacks, JSInSAR is able to provide reliable geophysical parameters in the presence of large coregistration errors. The effectiveness of the proposed technique is verified with a time series of high-resolution SAR data from the TerraSAR-X satellite.