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Interactive textbooks paired with online homework generate big data that can help answer questions about student engagement and learning. Here, a fully interactive textbook for a material and energy balances course measured over 1,300 reading interactions per student per cohort. In addition, several hundred auto-graded homework questions were assigned to students each semester. The auto-grading allowed for individual or class-level interventions to occur in real time and not after the next quiz or exam. In total, seven cohorts representing over 600 students and over 700,000 reading interactions are aggregated, which expands upon previous publications. For example, median reading participation was over 93% for all seven cohorts. In aggregate, female students completed reading participation at a higher rate than male students with statistical significance. Thus, applying some learning best practices including visuals and chunking in animations, immediate feedback in learning questions, and varying the interactive reading activities quantitatively engaged all learners, but showed even higher engagement with female students - an underrepresented group in engineering. Next, analytics from over 130,000 auto-graded problems are examined. Median correct of 91% or higher was found across six cohorts. Thus, allowing unlimited attempts on these formative problems allows students to persist in answering the randomized questions correctly. As with reading participation, female students completed a greater percentage of auto-graded problems than male students, however, statistical significance was not found for auto-graded problems. Overall, few articles in engineering education present data where an underrepresented group, female students in this case, outperform the majority group. While reasons for the differences are speculative at this point, we hope this contribution stimulates other qualitative and quantitative research on gender differences and educational technology. [ABSTRACT FROM AUTHOR]

The ASEE/AIChE Chemical Engineering Summer School (ChESS) is a week-long, roughly quinquennial over the past nearly 100 years, faculty development event bringing together early-career and seasoned faculty for workshops and community building [1]. The most recent ChESS took place July 25-29, 2022 at the Colorado School of Mines in Golden, CO, with around 160 participants and 80 presenters. The two core outcomes for the Summer School are 1) to build the Chemical Engineering education community and 2) to provide useful knowledge and tools for teaching, scholarship, and service for those early in their careers. A typical day at ChESS starts with breakfast and a plenary session, followed by one to two sessions with 5-6 parallel workshops, lunch, then two more parallel workshop sessions. These are complemented by thematic networking sessions, evening poster presentation receptions and a host of social events including a scavenger hunt. One afternoon of the week, local sightseeing and similar activities are available to all participants and presenters. Most workshops are delivered by volunteer presenters from the chemical engineering education community and about 20 are offered by industry and funding agency partners. Changes in programming for the most recent offering included specific identification of pedagogical, Diversity Equity and Inclusion (DEI), and content tracks for the parallel workshop sessions. To support this structure, plenary speakers were invited to present on pedagogical practices and DEI, in addition to the long-standing Teaching Institute and industry plenary. Workshops were either 90 or 150 minutes in length and typically hosted between 20-50 participants. While the core audience is newer faculty, the more experienced faculty who attend as workshop presenters are welcome to attend other workshops, space and time permitting, and about 90% of them did so. A survey conducted immediately after the close of ChESS 2022 showed respondents found it to be successful at meeting its two goals. 96% of respondents somewhat agreed or strongly agreed that the Summer School was conducive for meeting other Chemical Engineering faculty, while the same fraction somewhat agreed or strongly agreed that the workshops were useful. 93% of respondents strongly agreed that they would recommend the Summer School to a colleague, with a further 3% expressing some agreement. This paper shares details on the program, funding, and overall design of the Summer School as well as some reflections and recommendations from the steering committee. It also summarizes the results of the immediate post-Summer School survey. [ABSTRACT FROM AUTHOR]

Data science tools can help elucidate trends from clickstreams and other interactions generated by students actively using interactive textbooks. Specifically, data generated when using animations, which are multi-step visuals with text captions, will be presented in this work. Each animation step divides content into appropriate chunks, and so aligns with tenets of cognitive load theory. Both the quantity and timing of students' clicks record provide large data sets when examining students across hundreds of animations and multiple cohorts. Specifically, an interactive textbook for a chemical engineering course in Material and Energy Balances will be examined and build upon data presented previously. While most of the previous data focused on very high reading completion rates (>99% median) compared to traditional textbooks (20-50%), a deeper examination of how long students take when watching animations will be explored. With over 140 unique animations and tens of thousands of completed views over five cohorts, a spectral clustering algorithm applied to students' animation view times distinguished several types of animation watching behavior as well as monitor changes in this animation watching behavior over the course of a semester. After examining different numbers of clusters, two or three clusters in each chapter captured the animation usage. These clusters usually correspond to a group of students who watched animations at 1x speed (longer), another group who watched at 2x speed (shorter), and a third group, when present, who watched irregularly, including skipping animations. Overall, more students belonged to the belonged to the cluster with longer view times, with 63% of students aggregated over all cohorts and chapters compared to 35% of students in the cluster with shorter view times. The remaining 2% of students belonged to the irregular cluster, which was present in less than one quarter of the chapters. Many students stayed in the same cluster between chapters, while a smaller fraction switched between the longer and shorter clusters. [ABSTRACT FROM AUTHOR]

This evidence-based practice complete paper centers on the topics of assessment and learning technology for first-year engineering students. Spreadsheets are convenient for completing many calculations that engineering students and practicing engineers encounter. Spreadsheet programs are easily accessible and have been available for decades, including Microsoft Excel and Google Sheets; numerous formulas, functions, and other tasks are common across platforms. However, learning spreadsheet skills is usually limited to demonstration by an expert, such as numerous videos on YouTube. Here, an interactive textbook provided students the opportunity to acquire spreadsheet skills by performing spreadsheet actions. Various components of the interactive textbook apply learning theories including cognitive load, scaffolding, and deliberate practice. First, reading participation measured clicks from using interactive components, including multistep animations, multiple-choice questions, and matching exercises. Next, students had unlimited attempts to correctly answer over 120 auto-graded, randomized problems. In addition to basic spreadsheet skills and functions, advanced topics included solver, error, statistics, and matrix operations. In total, data generated by five cohorts (> 400 students) were studied. Median reading participation was very high - over 96% of 290 clicks per student - for all five cohorts. In addition, animation view rates were as high as 118%, indicating repetitive use. Animation view rates were higher for more advanced topics, such as double interpolation, compared to the basic skills and formulas. A median completion over 94% on auto-graded problems was observed for each of the five cohorts. By examining fraction correct on specific topics, real-time misconceptions and struggle can be noted by instructors, which leads to opportunities to provide interventions and facilitate learning. [ABSTRACT FROM AUTHOR]

Interactive textbooks generate big data through student reading participation, including animations, question sets, and auto-graded homework. Animations are multi-step, dynamic visuals with text captions. By dividing new content into smaller chunks of information, student engagement is expected to be high, which aligns with tenets of cognitive load theory. Specifically, students' clicks are recorded and measure usage, completion, and view time per step and for entire animations. Animation usage data from an interactive textbook for a chemical engineering course in Material and Energy Balances accounts for 60,000 animation views across 140+ unique animations. Data collected across five cohorts between 2016 and 2020 used various metrics to capture animation usage including watch and re-watch rates as well as the length of animation views. Variations in view rate and time were examined across content, parsed by book chapter, and five animation characterizations (Concept, Derivation, Figures and Plots, Physical World, and Spreadsheets). Important findings include: 1) Animation views were at or above 100% for all chapters and cohorts, 2) Median view time varies from 22 s (2-step) to 59 s (6-step) - a reasonable attention span for students and cognitive load, 3) Median view time for animations characterized as Derivation was the longest (40 s) compared to Physical World animations, which resulted in the shortest time (20 s). [ABSTRACT FROM AUTHOR]

Big data is driving decision making in many industries, and similar, quantitative assessments can be applied to engineering education when appropriate tools are deployed. In this study, a fully interactive online textbook, Material and Energy Balances zyBook, has been used to quantify reading and homework scores. In total, three cohorts of data representing over 280 students and almost 300,000 reading interactions are aggregated in this work. Recently presented results found median reading rates as high as 99% for over 1,300 interactions per student. However, all previously reported reading data was taken when reading assignments were due throughout the semester. New reading data taken at the conclusion of the semester found that many students completed reading without the incentive of earning a course grade. Both 1st quartile (capturing 75% of the class) reading rates and the fraction of the class completing 100% of the reading participation increased significantly after the due date. Additional reading after the due date encompassed 30 to 50 clicks by median and over 400 interactions for some students. [ABSTRACT FROM AUTHOR]

Spreadsheets provide a user-friendly environment to complete many calculations for engineering students as well as practicing engineers. Spreadsheet programs have been available for decades, including Microsoft Excel, Google Sheets, and many others; numerous formulas, functions, and other tasks are common across versions and platforms (e.g., Windows, Mac, iOS, Android). An interactive textbook from zyBooks titled Spreadsheets Essentials provides students opportunities to step through animations, complete question sets, and perform spreadsheet functions on autograded, randomized problems. Advanced topics include solver, error, statistics, interpolation, numerical integration, matrix operations, and more. The interactive format creates 'big data' on student behaviors, such as reading completion, auto-graded problem success, and auto-graded problem attempts. Providing nominal course credit led to very high reading rates in 2018. Specifically, at least 75% of students (n=98) completed 100% of the reading participation encompassing over 250 clicks across 12 sections. In addition, animation view rates quantified repetition with rates as high as 118%. Finally, success on over 100 auto-graded questions was higher for basic skills and formulas than more advanced topics, such as integration and interpolation. [ABSTRACT FROM AUTHOR]

This evidence-based practice paper discusses the preliminary validation of a project modified version of the Promoting Problem Solving Proficiency in First Year Engineering (PROCESS). The full rating plan required four raters to use the PROCESS to assess the problem-solving ability of ~70 engineering students randomly selected from two undergraduate cohorts at two Midwest universities. The many-facet Rasch measurement model has the psychometric properties to determine if there are any characteristics other than problem-solving that influence the scores assigned to students, such as rater bias or differential item functioning. Prior to implementing the full rating plan, the analysis examined how raters interacted with the six items on the modified PROCESS when scoring a random selection of 20 students' solutions to one textbook homework problem. Follow up inter-rater reliability meetings enabled rater discussion of rationale for discrepancies observed in the ratings. Differences in conceptions of the latent construct of problem-solving were resolved by recourse to the theoretical framework that informed the development of the PROCESS. This iterative process resulted in substantial increases in construct validity and measurement reliability when raters completed another round of assessment. Evidence indicated that raters increased their understanding of how rating scale categories related to levels of the latent construct. This paper describes the impacts and benefits this method of psychometric evaluation of rater-mediated assessments hold for the implementation of the full rating plan of student outcomes, as well as for the field of engineering education more broadly. [ABSTRACT FROM AUTHOR]

Textbook reading over many decades for higher education students is commonly reported at 30% or less. The objective of this paper is to integrate an existing static textbook with modern web tools to increase student interaction. Using a web-based platform called Perusall (perusall.com), students in a graduate course in fluid mechanics annotated a traditional textbook and journal papers. Students' questions about or comments on the readings were awarded a fraction of the total grade for the course. Features used to engage students in textbook readings will be discussed as well as example responses, scoring, inter-student discussions, faculty intervention, and end of semester survey. The quantity and quality of comments were graded using machine-learning algorithms built into the platform. Each comment was auto-graded on a 0, 1, or 2-point scale, the machine scoring agree very well with the professional judgment of the instructor. The spacing of comments across each assignment was accounted for also, which helps insure reading of the entire assignment. [ABSTRACT FROM AUTHOR]