Contribution: A model of tiered in-lab, compulsory lab programming sessions suitable for use in flipped learning environments. This article also addresses the scarcity of research that explores the effects of in-class activity organization. Background: When facing a subject they perceive as dry or difficult, some students may feel discouraged from making an effort to learn. Previous research has shown that students have a positive attitude toward assignment tiering, as a form of scaffolding, in voluntary, take-home assignments. Related models either are designed for different settings or have obvious problems with applicability in flipped learning environments. Intended Outcomes: A lab environment that motivates students to learn and consequently to perform better on in-class evaluations and on exams. The approach should be positively received by students. Application Design: Drawing upon the previous teaching experience, the proposed approach is a modification of an assignment tiering model found in the academic literature. With two gated tiered assignments per class, the steepness of the learning curve is alleviated for struggling students, while the injection of deliberate errors, reflexive questions, and ad hoc modification requests keep experienced students engaged with challenging tasks. Findings: The results of the six-year study, performed on an assembly language programming subject, are encouraging: Test groups were better in terms of motivation and performance, and the great majority of students expressed a positive attitude toward the new model.

This paper describes the application of folding technique to the Bit-Plane systolic FIR filter Architecture (BPA). We present the transformation of original DFG (Data Flow Graph) that enables the application of folding technique and the synthesis of fully pipelined folded architecture. The array is restricted for the factor in, where in represents the coefficient length. The number of basic cells in target architecture is reduced to the number of basic cells in one plane of source architecture. Also, the total number of latches corresponds to the number of latches in one plane of the BPA. The hardware restriction is paid by decreasing of throughput for slightly more than in times.

In this paper, we propose a framework for evaluation of cross-lingual performance of AI text detection tools. The framework consists of the sample selection methodology and a statistical apparatus. To illustrate the use of the proposed framework, performances of five AI text detectors in English, representing a larger linguistic domain, and Serbian, representing a smaller linguistic domain, are compared. The analysis also investigated the impact of automatic translation on detectors' performance. Results indicate that, as expected, detectors perform better for English texts, but there is an instance where performance is comparable for Serbian. Additionally, a case was found where automatic translation can mislead detectors. This study should shed light on limitations and capabilities of existing detection technologies and potential directions for improvement.