Leen-Kiat Soh

• University of Nebraska–Lincoln

Museum collection databases contain echoes of encounter between colonial collectors (broadly defined) and Indigenous people from around the world. The moment of acquisition—when an item passed out of a community and into the hands of the collector—often included multilingual acts of translation. An artist may have shared the Indigenous name of the...

Background and Context: Professional development (PD) programs for K-12 computer science teachers use surveys to measure teachers’ knowledge and attitudes while recognizing daily sentiment and emotion changes can be crucial for providing timely teacher support. Objective: We investigate approaches to compute sentiment and emotion scores automatica...

Human and natural processes such as navigation and natural calamities are intrinsically linked to the geographic space and described using place names. Extraction and subsequent geocoding of place names from text are critical for understanding the onset, progression, and end of these processes. Geocoding place names extracted from text requires usi...

In many real‐world applications of AI, the set of actors and tasks are not constant, but instead change over time. Robots tasked with suppressing wildfires eventually run out of limited suppressant resources and need to temporarily disengage from the collaborative work in order to recharge, or they might become damaged and leave the environment per...

Image downscaling is an essential operation to reduce spatial complexity for various applications and is becoming increasingly important due to the growing number of solutions that rely on memory-intensive approaches, such as applying deep convolutional neural networks to semantic segmentation tasks on large images. Although conventional content-in...

Diving below the surface has its challenges, however. For example, “noise effects” are especially widespread when digital images have been created from earlier microphotographic copies, as is common in historical newspaper collections. Noise effects introduce interference to the primary signals of the pages, both for human vision and computer visio...

The 2023 SIGCSE Technical Symposium has come to a close. Thank you, all 1,554 of you, that joined us in Toronto and online for the first-ever SIGCSE Technical Symposium held outside the United States. We enjoyed welcoming 1,354 of you to Canada in person, as well as an additional 200 of you who registered for online attendance. While we didn't set...

Objectives . Although prior research has uncovered shifts in computer science (CS) students’ implicit beliefs about the nature of their intelligence across time, little research has investigated the factors contributing to these changes. To address this gap, two studies were conducted in which the relationship between ineffective self-regulation of...

Prior research suggests that the timing and location of social unrest may be influenced by similar unrest activities in another nearby region, potentially causing a spread of unrest activities across space and time. In this paper, we model the spread of social unrest across time and space using a novel approach, grounded in agent-based modeling (AB...

The 2023 SIGCSE Technical Symposium will take place from March 15 - 18, 2023, at the Metro Toronto Convention Centre in Toronto, Canada. We look forward to welcoming you to Canada for the first ever SIGCSE Technical Symposium outside of the United States. The program for the 2023 Technical Symposium is online now. It is a diverse program that showc...

Application Programming Interfaces (APIs) in cryptography typically impose concealed usage constraints. The violations of these usage constraints can lead to software crashes or security vulnerabilities. Several professional tools can detect these constraints (API misuses) in cryptography; however, in the educational programs, the focus has been le...

Place names facilitate locating and distinguishing geographic space where human activities and natural phenomena occur. Extracting place names at multiple spatial resolutions from text is beneficial in several tasks such as identifying the location of events, enriching gazetteers, discovering connections between events and places, etc. Most modern...

The SIGCSE TS is a forum for educators and researchers to share new results and insights around developing, implementing, or evaluating computing programs, pedagogy, curricula, and courses. The conference is planned to be held in Toronto, Ontario and will offer hybrid participation.

Two studies investigated change in computer science (CS) students’ implicit intelligence beliefs. Across both studies, we found that the strength of incremental and entity beliefs changed across time. In Study 1, we found that incremental beliefs decreased and entity beliefs increased across the semester. Change in implicit intelligence beliefs was...

Computer science students have difficulty understanding correct usages of an Application Programming Interface (API) and programming violations that cause compilation or runtime errors. Despite high-quality documentation for programming, the students typically need an instructor's feedback when their programs cause bugs, crashes, and vulnerabilitie...

The successful use of deep learning solutions for document image segmentation typically relies on a large number of manually labeled groundtruth examples, which is expensive to obtain for historical document images that have significant noise effects and variation. At the same time, successful applications of deep learning solutions for document im...

Intertemporal choices involve assessing options with different reward amounts available at different time delays. The similarity approach to intertemporal choice focuses on judging how similar amounts and delays are. Yet we do not fully understand the cognitive process of how these judgments are made. Here, we use machine-learning algorithms to pre...

Contribution: This article presents a synthesis of the findings and implications from the IC2Think program of research in undergraduate computer science (CS) courses examining student motivation and self-regulated learning (SRL). These studies illuminate both the difficulty and potential for motivating CS students, as well as the uniqueness of CS a...

In geographic data analysis, it is often the case that multiple aspects of a single phenomenon are captured by different sources of data. For instance, a storm can be identified based on its precipitation, as well as windspeed, and changes in barometric pressure. It proves beneficial in specific domains to be able to use all available sources of da...

Intertemporal choices involve assessing options with different reward amounts available at different time delays. The similarity approach to intertemporal choice focuses on judging how similar amounts and delays are, yet we do not fully understand the cognitive process of how these judgments are made. Here, we use machine-learning algorithms to pre...

Rising enrollments in Computer Science pose an opportunity to engage students from diverse backgrounds and interests; and a challenge to deliver on positive learning outcomes. While student engagement is the driving factor for increased learning performance and retention, it has been declining to new lows for Computer Science students in recent yea...

In open agent systems, the set of agents that are cooperating or competing changes over time and in ways that are nontrivial to predict. For example, if collaborative robots were tasked with fighting wildfires, they may run out of suppressants and be temporarily unavailable to assist their peers. We consider the problem of planning in these context...

Calls for standardized and validated measures of computational thinking have been made repeatedly in recent years. Still, few such tests have been created and even fewer have undergone rigorous psychometric evaluation and been made available to researchers. The purpose of this study is to report our work in developing and validating a test of compu...

Increasing retention in computer science (CS) courses is a goal of many CS departments. A key step to increasing retention is to understand the factors that impact the likelihood students will continue to enroll in CS courses. Prior research on retention in CS has mostly examined factors such as prior exposure to programming and students’ personali...

From July 16-to November 8, 2019, the Aida digital libraries research team at the University of Nebraska-Lincoln collaborated with the Library of Congress on “Digital Libraries, Intelligent Data Analytics, and Augmented Description: A Demonstration Project.“ This demonstration project sought to (1) develop and investigate the viability and feasibil...

This presentation to Library of Congress staff, delivered onsite on January 10, 2020, presents a tour through the demonstration project pursued by the Aida digital libraries research team with the Library of Congress in 2019-2020. In addition to providing an overview and analysis of the specific machine learning projects scoped and explored, this p...

In open agent systems, the set of agents that are cooperating or competing changes over time and in ways that are nontrivial to predict. For example, if collaborative robots were tasked with fighting wildfires, they may run out of suppressants and be temporarily unavailable to assist their peers. We consider the problem of planning in these context...

Includes framing, overview, and discussion of the explorations pursued as part of the Digital Libraries, Intelligent Data Analytics, and Augmented Description demonstration project, pursued by members of the Aida digital libraries research team at the University of Nebraska-Lincoln through a research services contract with the Library of Congress....

This presentation summarized and presented preliminary results from the first weeks of work conducted by the Aida research team in response to Library of Congress funding notice ID 030ADV19Q0274, “The Library of Congress – Pre-processing Pilot.” It includes overviews of projects on historic document segmentation, document classification, document q...

Computer science (CS) courses are taught with increasing emphasis on group work and with non-programming exercises facilitating peer-based learning, computational thinking, and problem solving. However, relatively little work has been done to investigate the interaction of group work and non-programming exercises because collaborative, non-programm...

In this workshop, participants will learn how to integrate in their classes computational thinking and creative thinking activities that have been shown via rigorous research to significantly improve student learning and performance. Specifically, participants will be familiarized with the suite of Computational Creativity Exercises (non-programmin...

In recent years, a growing number of universities have begun to offer specialized courses as a way to make computer science (CS) more accessible to students with little or no prior CS or programming experience, especially non-CS majors. One of the ways courses have been modified for these students is by supplementing the core problem solving and co...

This document includes work-in-progress reports submitted to the Library of Congress as part of the Aida digital libraries research team's work on Digital Libraries, Intelligent Data Analytics, and Augmented Description: A Demonstration Project. These work-in-progress reports provide a snapshot glimpse, as well as underlying rationale and decision-...

This presentation situates the work of the Aida team broadly as well as hinges this work on some very specific challenges for digital libraries. In doing so demonstrate the many types of questions and domains to be explored in digitized newspapers.

With the increasing ubiquity of computing, more engineering programs now require their students to take one or more computing courses. At institutions where significant numbers of engineering students take computer courses, computing instructors and educators often assume roles that have them teaching their computing courses for non-majors as servi...

Within the context of mass-scale digital libraries, this panel will explore methodologies and uses for-as well as the results of- conceiving of "data as collections" and "collections as data." The panel will explore the implications of these concepts through use cases involving data mining of the HathiTrust Digital Library, particularly major proje...

We describe an intelligent image analysis approach to automatically detect poems in digitally archived historic newspapers. Our application, Image Analysis for Archival Discovery, or Aida, integrates computer vision to capture visual cues based on visual structures of poetic works—instead of the meaning or content—and machine learning to train an a...

In this paper, a multiagent-based model is used to study distributed energy management in a microgrid (MG). The suppliers and consumers of electricity are modeled as autonomous agents, capable of making local decisions in order to maximize their own profit in a multiagent environment. For every supplier, a lack of information about customers and ot...

This research investigated the relationships among undergraduate computer science students’ computer-science-related career aspirations, perceived instrumentality (PI) for computer science courses, and achievement in those courses. Specifically, the two studies examined (a) change in PI and career aspirations during a single semester, (b) the relat...

Contribution: This paper provides evidence that computational creativity exercises (CCEs) can increase engineering students' learning in introductory computer science (CS1) courses. Its main contribution is its more rigorous treatment/control group research design that allows testing for causal influences of CCEs on student learning and performance...

In this workshop, we will introduce you to a suite of Computational Creativity Exercises (CCEs) that have been shown to significantly improve student learning and achievement in introductory and advanced CS courses. CCEs address core aspects of computational thinking while exposing students to creative thinking skills, and can be adapted for use in...

The purpose of the present study was to investigate how the inclusion of computational creativity exercises (CCEs) merging computational and creative thinking in undergraduate computer science (CS) courses affected students' course grades, learning of core CS knowledge, self-efficacy, and creative competency. CCEs were done in lower- and upper-divi...

Retaining students in computer science (CS) courses and majors is a concern for many undergraduate CS programs in the United States. A large proportion of students who initially declare a major in CS do not complete a CS degree. The impact of future-oriented motivational constructs such as career aspirations and future connectedness on retention ha...

This presentation Reads digital library interfaces—or their "main door" interfaces—as glimpses into what we have thus far valued in the development of digital libraries Frames a visual way of thinking about textual materials Introduces the work of our research team—where we are now, and where we're headed Draws some connections between the parts Th...

The National Science Foundation-Census Bureau Research Network (NCRN) was established in 2011 to create interdisciplinary research nodes on methodological questions of interest and significance to the broader research community and to the Federal Statistical System (FSS), particularly to the Census Bureau. The activities to date have covered both f...

Similarity models of intertemporal choice are heuristics that choose based on similarity judgments of the reward amounts and time delays. Yet, we do not know how these judgments are made. Here, we use machine-learning algorithms to assess what factors predict similarity judgments and whether decision trees capture the judgment outcomes and process....

Social Unrest Reconnaissance Gazetteer (or SURGE) is a Web-based application that provides an open system to visualize and integrate spatio-temporal data about social unrest events with related data layers in South Asia to facilitate data-driven as well as model-based investigations and analyses. Currently, the system displays eight categories of u...

Computational thinking and creative thinking are valuable tools both within and outside of computer science (CS). The goal of the project discussed here is to increase students' achievement in CS courses through a series of computational creativity exercises (CCEs). In this paper, the framework of CCEs is described, and the results of two separate...

Image snippets and analysis files for the Aida team's case study of poetic content in digitized newspapers from Chronicling America, covering the period 1836-1840. Images were downloaded from Chronicling America as JPEG2000, converted to JPG, cut up into overlapping image snippets, and processed with various blurring algorithims. Feature values wer...

Our research is based on an innovative approach that integrates computational thinking and creative thinking in computer science courses to improve student learning and performance. Referencing Epstein's Generativity Theory, we designed and deployed Computational Creativity Exercises (CCEs) with linkages to concepts in computer science and computat...

This study investigated introductory computer science (CS1) students' implicit beliefs of intelligence. Referencing Dweck and Leggett's (1988) framework for implicit beliefs of intelligence, we examined how (1) students' implicit beliefs changed over the course of a semester, (2) these changes differed as a function of course enrollment and student...

Determining which verbal behaviors of interviewers and respondents are dependent on one another is a complex problem that can be facilitated via data-mining approaches. Data are derived from the interviews of 153 respondents of the Panel Study of Income Dynamics (PSID) who were interviewed about their life-course histories. Behavioral sequences of...

We explored CS1 students' perceived instrumentality (PI) for the course and aspirations for a career related to CS. Perceived instrumentality refers to the connection one sees between a current activity and a future goal. There are two types of PI: endogenous and exogenous. Endogenous instrumentality refers to the perception that mastering new info...

Chunking has emerged as a basic property of human cognition. Computationally, chunking has been proposed as a process for compressing information also has been identified in neural processes in the brain and used in models of these processes. Our purpose in this paper is to expand understanding of how chunking impacts both learning and performance...

The goal of this study was to investigate how students' entering motivation for the course in a suite of CS1 introductory computer science courses was associated with their subsequent course achievement and retention. Courses were tailored for specific student populations (CS majors, engineering majors, business-CS combined honors program). Student...

Introductory computer science courses are being increasingly taught using technology-mediated instruction and e-learning environments. The software and technology in such courses could benefit from the use of student models to inform and guide customized support tailored to the needs of individual students. In this paper, we investigate how student...

Survey informatics leverages two separate but vital areas of research--survey methodology and computer science and engineering--to advance the state of the art in each and improve our understanding of the human experience.

Students’ motivation and strategic engagement have been identified as playing crucial roles in their success in STEM and CS classes. Numerous motivational constructs have been identified including goals, instrumentality of the course, mindsets, emotional/affective reactions, and self-efficacy. These are thought to motivate students’ to achieve and...

Creative Thinking, Computational Thinking Exercises | Overall Design & Examples Results | Brief Overview Logistics | Tips, Support & Feedback Aim to improve the learning of computational thinking by blending it with creative thinking Creative thinking? • Patterned in a way that tends to lead to creative results • Not limited to the arts • An integr...

This study investigated the predictors of support for and resistance to hacktivism in a sample of 78 science, technology, engineering, and mathematics majors at a Midwestern university. Results from surveys about real-world instances of hacktivism indicate different preexisting global attitudes predict specific situational hacktivism support (predi...

Improving learning and achievement in introductory computer science by incorporating creative thinking into the curriculum.

Our study was based on exploring CS1 students' implicit theories of intelligence. Referencing Dweck and Leggett's [5] framework for implicit theories of intelligence, we investigated (1) how students' implicit theories changed over the course of a semester, (2) how these changes differed as a function of course enrollment and students' self-regulat...

The Image Analysis for Archival Discovery (Aida) project team is investigating the use of image analysis to identify poetic content in historic newspapers. The project seeks both to augment the study of literary history by drawing attention to the magnitude of poetry published in newspapers and by making the poetry more readily available for study,...

Self-efficacy is a person's subjective confidence in their capability of effectively executing behaviors and actions including problem solving. Research has shown it to be one of the most powerful motivators of human action and strongest predictors of performance across a variety of domains. This paper reports on the computational modeling of self-...

In this paper, we address the problem of suboptimal behavior during online partially observable Markov decision process (POMDP) planning caused by time constraints on planning. Taking inspiration from the related field of reinforcement learning (RL), our solution is to shape the agent’s reward function in order to lead the agent to large future rew...

Students' goal orientations impact their self-regulation, engagement, and achievement in post-secondary STEM courses. But, how students' goal orientations change across a semester and the impacts of these changes have not been extensively studied. Study purposes were to investigate goal orientation change across the semester, associations of goal c...

Promoting computational thinking is a priority in CS education and other STEM and non-STEM disciplines. Our innovative, NSF-funded IC2Think project blends computational and creative thinking. In Spring 2013, we deployed Computational Creativity Exercises (CCE) designed to engage creative competencies (Surrounding, Capturing, Challenging and Broaden...

Agents operating in complex (e.g., dynamic, uncertain, partially observable) environments must gather information from various sources to inform their incomplete knowledge. Two popular types of sources include: (1) directly sensing the environment using the agent's sensors, and (2) sharing information between networked agents occupying the same env...

When deciding which ad hoc team to join, agents are often required to consider rewards from accomplishing tasks as well as potential benefits from learning when working with others, when solving tasks. We argue that, in order to decide when to learn or when to solve task or both, agents have to consider the existing agents' capabilities and tasks a...

Background Technical, nonengineering required courses taken at the onset of an engineering degree provide students a foundation for engineering coursework. Students who perform poorly in these foundational courses, even in those tailored to engineering, typically have limited success in engineering. A profile approach may explain why these courses...

Self-efficacy is defined as a person's subjective confidence in their capability of executing an action and has been shown to be one of the most powerful motivators of human action predicting performance across a variety of domains. Self-efficacy has been associated with brain level neural processes and efficacy-like confidence mechanisms are incor...

The smart grid of the future may equip customers with distributed generation and storage systems that can change their overall demand behavior. Indeed, the smart grid's infrastructure provides new opportunities for the grid and its customers to exchange information regarding real-time electricity rates and demand profiles. Here we report on innovat...

Heuristic search algorithms for online POMDP planning have shown great promise in creating successful policies for maximizing agent rewards using heuristics typically focused on reducing the error bound in the agent's cumulative future reward estimations. However, error bound-based heuristics are less informative in highly uncertain domains requiri...

Our research is based on an innovative approach that integrates computational thinking and creative thinking in CS1 to improve student learning performance. Referencing Epstein's Generativity Theory, we designed and deployed a suite of creative thinking exercises with linkages to concepts in computer science and computational thinking, with the pre...

Widespread use of GPS devices and ubiquity of remotely sensed geospatial images along with cheap storage devices have resulted in vast amounts of digital data. More recently, with the advent of wireless technology, a large number of sensor networks have been deployed to monitor many human, biological and natural processes. This poses a challenge in...

Boosting is an iterative process that improves the predictive accuracy for supervised (machine) learning algorithms. Boosting operates by learning multiple functions with subsequent functions focusing on incorrect instances where the previous functions predicted the wrong label. Despite considerable success, boosting still has difficulty on data se...

Real-world datasets often contain large numbers of unlabeled data points, because there is additional cost for obtaining the labels. Semi-supervised learning (SSL) algorithms use both labeled and unlabeled data points for training that can result in higher classification accuracy on these datasets. Generally, traditional SSLs tentatively label the...