This paper proposes to evaluate learning efficiency by implementing the flipped classroom and automatic source code evaluation based on the Kirkpatrick evaluation model in students of CS1 programming course. The experimentation was conducted with 82 students from two CS1 courses; an experimental group (EG = 56) and a control group (CG = 26). Each…

Despite the increasing adaption of automated text analysis in communication studies, its strengths and weaknesses in framing analysis are so far unknown. Fewer efforts have been made to automatic detection of networked frames. Drawing on the recent developments in this field, we harness a comparative exploration, using Latent Dirichlet Allocation…

To identify the dominant cultural models among parents transmitting faith to their children, we find few methodological guidelines to guide coding and analysis of semi-structured interviews. We thus developed a three-phase procedure for our research team. Phase-one follows Campbell et al. by unitizing on meanings rather than words/pages, including…

Assessing students' participation in science practices presents several challenges, especially when aiming to differentiate meaningful (vs. rote) forms of participation. In this study, we sought to use machine learning (ML) for a novel purpose in science assessment: developing a construct map for students' "consideration of generality,"…

Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…

As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…

This paper provides a tutorial on epistemic network analysis (ENA), a novel method for identifying and quantifying connections among elements in coded data and representing them in dynamic network models. Such models illustrate the structure of connections and measure the strength of association among elements in a network, and they quantify…

Collecting (or "sampling") information that one expects to be useful is a powerful way to facilitate learning. However, relatively little is known about how people decide which information is worth sampling over the course of learning. We describe several alternative models of how people might decide to collect a piece of information…

As a response to accountability and pressure from the No Child Left Behind Act of 2002, the South Dakota Department of Education informed school administrators of a state-wide transformation of the way districts measure teacher effectiveness in their schools. In 2011, "The Framework for Teaching Evaluation Instrument" (Danielson, 2002)…

Piecewise growth models (PGMs) were used to estimate and model changes in the preliteracy skill development of kindergartners in a moderately sized school district in the Pacific Northwest. PGMs were applied to interrupted time-series (ITS) data that arose within the context of a response-to-intervention (RtI) instructional framework. During the…

A new "controlled assessment" model was introduced in England, Wales and Northern Ireland in 2009. This paper describes a research project that explores teachers' experiences of this new assessment model in General Certificate of Secondary Education (GCSE) level modern foreign language (MFL) speaking assessment. Focusing on teachers'…

This study aimed at investigating the extent to which secondary schools mathematics teachers practice to assessment models in their mathematics teaching and learning. Definitely, the study aimed at answering the following questions: (1) To what extent do secondary schools mathematics teachers practice each of the assessment models in their…

We present a new method for analyzing a student's learning over time for a specific skill: analysis of the graph of the student's moment-by-moment learning over time. Moment-by-moment learning is calculated using a data-mined model that assesses the probability that a student learned a skill or concept at a specific time during learning (Baker,…

The continuously growing demand for program results has produced an increased need for evaluation capacity building (ECB). The "Integrative ECB Model" was developed to integrate concepts from existing ECB theory literature and to structure a synthesis of the empirical ECB literature. The study used a broad-based research synthesis method with…

Early on during word recognition, letter positions are not accurately coded. Evidence for this comes from transposed-letter (TL) priming effects, in which letter strings generated by transposing two adjacent letters (e.g., "jugde") produce large priming effects, more than primes with the letters replaced in the corresponding position (e.g.,…