The tools used in learning processes are in a continuous state of flux. One of the most significant changes is the application of Information and Communications technologies (ICTs) to educational contexts. This provides new possible ways to carry out learning activities, new learning services, the possibility to use new kinds of contents and activities, etc. However, ICTs have not provided as many advantages as they were supposed to, so changes are necessary. In this context, a new set of tools, Web 2.0, offers a new way to understand the Web, in which the user is the centre. Further, users can cooperate in order to define contents. This concept is also applied in technology-mediated learning but there are important problems when one tries to integrate such tools and concepts with existing systems. This paper explores the integration of these tools in traditional learning environments, the various possibilities and their advantages and drawbacks. After that, an interoperability scenario is described and two experiences are presented to show how 2.0 tools can be integrated in learning activities, and its effect in educational process.

This study investigates the contribution of potential sources to the submicron (PM₁) organic aerosol (OA) simultaneously detected at an urban background (UB) and a road site (RS) in Barcelona during the 30 days of the intensive field campaign of SAPUSS (Solving Aerosol Problems by Using Synergistic Strategies, September–October 2010). A total of 103 filters at 12 h sampling time resolution were collected at both sites. Thirty-six neutral and polar organic compounds of known emission sources and photo-chemical transformation processes were analyzed by gas chromatography–mass spectrometry (GC-MS). The concentrations of the trace chemical compounds analyzed are herein presented and discussed. Additionally, OA source apportionment was performed by multivariate curve resolution–alternating least squares (MCR-ALS) and six OA components were identified at both sites: two were of primary anthropogenic OA origin and three of secondary OA origin, while a sixth one was not clearly defined. Primary organics from emissions of local anthropogenic activities (urban primary organic aerosol, or POA Urban), mainly traffic emissions but also cigarette smoke, contributed 43% (1.5 μg OC m⁻³) and 18% (0.4 μg OC m⁻³) to OA at RS and UB, respectively. A secondary primary source – biomass burning (BBOA) – was found in all the samples (average values 7% RS; 12% UB; 0.3 μg OC m⁻³), but this component was substantially contributing to OA only when the sampling sites were under influence of regional air mass circulation (REG.). Three secondary organic aerosol (SOA) components (describing overall 60% of the variance) were observed in the urban ambient PM₁. Products of isoprene oxidation (SOA ISO) – i.e. 2-methylglyceric acid, C₅ alkene triols and 2-methyltetrols – showed the highest abundance at both sites when the city was under influence of inland air masses. The overall concentrations of SOA ISO were similar at both sites (0.4 and 0.3 μg m⁻³, or 16% and 7%, at UB and RS, respectively). By contrast, a SOA biogenic component attributed to α-pinene oxidation (SOA BIO PIN) presented average concentrations of 0.5 μg m⁻³ at UB (24% of OA) and 0.2 μg m⁻³ at RS (7%), respectively, suggesting that this SOA component did not impact the two monitoring sites at the same level. A clear anti-correlation was observed between SOA ISO and SOA PIN during nucleation days, surprisingly suggesting that some of the growth of urban freshly nucleating particles may be driven by biogenic α-pinene oxidation products but inhibited by isoprene organic compounds. A third SOA component was formed by a mixture of aged anthropogenic and biogenic secondary organic compounds (SOA Aged) that accumulated under stagnant atmospheric conditions, contributing for 12% to OA at RS (0.4 μg OC m⁻³) and for 18% at UB (0.4 μg OC m⁻³). A sixth component, formed by C₇–C₉ dicarboxylic acids and detected especially during daytime, was called "urban oxygenated organic aerosol" (OOA Urban) due to its high abundance at urban RS (23%; 0.8 μg OCm⁻³) vs. UB (10%; 0.2 μg OCm⁻³), with a well-defined daytime maximum. This temporal trend and geographical differentiation suggests that local anthropogenic sources were determining this component. However, the changes of these organic molecules were also influenced by the air mass trajectories, indicating that atmospheric conditions have an influence on this component, although the specific origin on this component remains unclear. It points to a secondary organic component driven by primary urban sources including cooking and traffic (mainly gasoline) activities.

Most educational software programs use and gather personal information and metadata from students. Additionally, most of the educational software programs are no longer operated by the learning institutions but are run by third-party agencies. This means that in the decade since 2020, information about students is stored and handled outside premises and control of learning institutions. The personal information about students and their activity while they interact with learning management systems and online learning tools is increasingly in custody of cloud computing platforms, software-as-a-service providers, and learning tool vendors. There is an increasing will to use all the data and metadata from the activity of the students for research, to develop education management strategies, pedagogy approaches, and develop behavior control tools or learning tools informed by behavior analysis from learning analytics. Many times, these studies lack the ethical and moral perspective. In addition, there is an increasing number of cases in which this information has leaked or has been used in a shady way. Additionally, this information will be around for a long time, tied to the future digital profiles of the students whose data has been leaked. This paper hypothesizes that there has been an ongoing process of technological evolution that leads to a loss of control over personal information, which makes it even more difficult to protect user confidentiality and ensuring privacy, that data surveillance has entered the world of education, and that the current legal frameworks are not enough to really protect the student’s personal information. The paper analyzes how this situation came to pass, and why this is wrong. We conclude with some proposals to address it from its different root dimensions: technical, cultural, legal, and organizational.