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The litter bag technique was used to study leaf decomposition in the large forested eutrophic (160.9 μmol l–1 DIN, 1.7 μmol l–1 SRP) Ebro river and in the forested Sènia (12.8 μmol l–1 DIN, 0.7 μmol l–1 RSP). Air dried leaves (3g) of Phragmites australis were used in both watercourses while Populus alba leaves were studied in the Ebro river only, and Populus nigra leaves and a submerged rooted macrophyte (stems and leaves), Potamogeton coloratus, were studied only in the Sènia stream. Litter bags of 100 μm and 1 mm mesh size were collected on days 0, 3, 15, 30, 90 and 120 and 5 mm mesh bags were sampled once after 30 days. Macroinvertebrates inside the leaf bags were retrieved and ash free dry weight and carbon and nitrogen contents of the remaining detritus were determined. Litter decomposition rates, k, were estimated using a simple exponential model. No significant differences in decomposition rates were observed between 100 μm and 1 mm mesh bags. In 100 μm litter bags, decomposition of P. nigra leaves from the Sènia stream (0.0104 day–1) was faster than that of P. alba leaves from the Ebro river (0.0049 day–1) (ANCOVA, p < 10–5). The decomposition rate of P. australis was higher in the Ebro river (0.009 ± 0.002 day–1) than in the Sènia stream (0.0056 ± 0.0004 day–1) for the first 30 days of decomposition, but no differences were observed from day 30 onwards. The number of macroinvertebrates increased over time and were mainly collectors‐gatherers of the genus Chironomus. Percentage of detritus nitrogen increased in litter that had initially high C/N ratios (28.7 in P. alba and 64.7 in P. nigra) and decreased when initial C/N ratios were low (12.6 and 14.6 for P. australis from the Sènia and Ebro river respectively).

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Computational thinking (CT) skills are becoming increasingly relevant for future professionals across all domains, beyond computer science (CS). As such, an increasing number of bachelor's and master's programs outside of the CS discipline integrate CT courses within their study program. At the same time, tools such as notebooks and interactive apps designed to support the teaching of programming concepts are becoming ever more popular. However, in non-CS majors, CT might not be perceived as essential, and students might lack the motivation to engage with such tools in order to acquire solid CT skills. This article presents a field study conducted with 115 students during a full semester on a novel computational notebook environment. It evaluates computational notebooks and CT skills in an introductory course on information technology for first-year undergraduates in business and economics. A multidimensional evaluation approach makes use of pre-and post-test surveys, lectures, and self-directed laboratory sessions tracking analytics. Our findings suggest that, in the process of learning CT for non-CS students, engagement in active learning activities can be a stronger determinant of learning outcomes than initial knowledge. Furthermore, gamifying computational notebooks can serve as a strong driver of active learning engagement, even more so than initial motivational factors.