Search for: All records

This study investigated uniform differential item functioning (DIF) detection in response times. We proposed a regression analysis approach with both the working speed and the group membership as independent variables, and logarithm transformed response times as the dependent variable. Effect size measures such as Δ[Formula: see text] and percentage change in regression coefficients in conjunction with the statistical significance tests were used to flag DIF items. A simulation study was conducted to assess the performance of three DIF detection criteria: (a) significance test, (b) significance test with Δ[Formula: see text], and (c) significance test with the percentage change in regression coefficients. The simulation study considered factors such as sample sizes, proportion of the focal group in relation to total sample size, number of DIF items, and the amount of DIF. The results showed that the significance test alone was too strict; using the percentage change in regression coefficients as an effect size measure reduced the flagging rate when the sample size was large, but the effect was inconsistent across different conditions; using Δ R²with significance test reduced the flagging rate and was fairly consistent. The PISA 2018 data were used to illustrate the performance of the proposed method in a real dataset. Furthermore, we provide guidelines for conducting DIF studies with response time. 

This Brief Report presents an example of assessment validation using an argument-based approach. The instrument we developed is a Brief Assessment of Students’ Mature Number Sense, which measures a central goal in mathematics education. We chose to develop this assessment to provide an efficient way to measure the effect of instructional practices designed to improve students’ number sense. Using an argument-based framework, we first identify our proposed interpretations and uses of student scores. We then outline our argument with three claims that provide evidence connecting students’ responses on the assessment with its intended uses. Finally, we highlight why using argument-based validation benefits measure developers as well as the broader mathematics education community. 

Cellular network control procedures (e.g., mobility, idle-active transition to conserve energy) directly influence data plane behavior, impacting user-experienced delay. Recognizing this control-data plane interdependence, L25GC re-architects the 5G Core (5GC) network, and its processing, to reduce latency of control plane operations and their impact on the data plane. Exploiting shared memory, L25GC eliminates message serialization and HTTP processing overheads, while being 3GPP-standards compliant. We improve data plane processing by factoring the functions to avoid control-data plane interference, and using scalable, flow-level packet classifiers for forwarding-rule lookups. Utilizing buffers at the 5GC, L25GC implements paging, and an intelligent handover scheme avoiding 3GPP's hairpin routing, and data loss caused by limited buffering at 5G base stations, reduces delay and unnecessary message processing. L25GC's integrated failure resiliency transparently recovers from failures of 5GC software network functions and hardware much faster than 3GPP's reattach recovery procedure. L25GC is built based on free5GC, an open-source kernel-based 5GC implementation. L25GC reduces event completion time by ~50% for several control plane events and improves data packet latency (due to improved control plane communication) by ~2×, during paging and handover events, compared to free5GC. L25GC's design is general, although current implementation supports a limited number of user sessions.