Cognitive emotions in e-learning processes and their potential relationship with students’ academic adjustment

In times of growing importance and emphasis on improving academic outcomes for young people, their academic selves/lives are increasingly becoming more central to their understanding of their own wellbeing. How they experience and perceive their academic successes or failures, can influence their perceived self-efficacy and eventual academic achievement. To this end, ‘cognitive emotions’, elicited to acquire or develop new skills/knowledges, can play a crucial role as they indicate the state or the “flow” of a student’s emotions, when facing challenging tasks. Within innovative teaching models, measuring the affective components of learning have been mainly based on self-reports and scales which have neglected the real-time detection of emotions, through for example, recording or measuring facial expressions. The aim of the present study is to test the reliability of an ad hoc software trained to detect and classify cognitive emotions from facial expressions across two different environments, namely a video-lecture and a chat with teacher, and to explore cognitive emotions in relation to academic e-selfefficacy and academic adjustment. To pursue these goals, we used video-recordings of ten psychology students from an online university engaging in online learning tasks, and employed software to automatically detect eleven cognitive emotions. Preliminary results support and extend prior studies, illustrating how exploring cognitive emotions in real time can inform the development and success of academic e-learning interventions aimed at monitoring and promoting students’ wellbeing.peer-reviewe

Tackling the Challenging Determination of Trace Elements in Ultrapure Silicon Carbide by LA-ICP-MS

The goal of accurately quantifying trace elements in ultrapure silicon carbide (SiC) with a purity target of 5N (99.999% purity) was addressed. The unsuitability of microwave-assisted acid digestion followed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS) analysis was proved to depend mainly on the contamination induced by memory effects of PTFE microwave vessels and by the purity levels of acids, even if highly pure ones were used in a clean environment. A new analytical protocol for the direct analysis of the solid material by laser ablation coupled with ICP-MS (LA-ICP-MS) was then exploited. Different samples were studied; the best results were obtained by embedding SiC (powders or grains) in epoxy resin. This technique has the great advantage of avoiding any source of external contamination, as grinding, pressing and sintering pretreatments are totally unnecessary. Two different laser wavelengths (266 and 193 nm) were tested, and best results were obtained with the 266 nm laser. The optimized protocol allows the determination of elements down to the sub-mg/kg level with a good accuracy level

Cognitive emotions in E-learning processes and their potential relationship with students' academic adjustment

In times of growing importance and emphasis on improving academic outcomes for young people, their academic selves/lives are increasingly becoming more central to their understanding of their own wellbeing. How they experience and perceive their academic successes or failures, can influence their perceived self-efficacy and eventual academic achievement. To this end, 'cognitive emotions', elicited to acquire or develop new skills/knowledges, can play a crucial role as they indicate the state or the "flow" of a student's emotions, when facing challenging tasks. Within innovative teaching models, measuring the affective components of learning have been mainly based on self-reports and scales which have neglected the real-time detection of emotions, through for example, recording or measuring facial expressions. The aim of the present study is to test the reliability of an ad hoc software trained to detect and classify cognitive emotions from facial expressions across two different environments, namely a video-lecture and a chat with teacher, and to explore cognitive emotions in relation to academic e-selfefficacy and academic adjustment. To pursue these goals, we used video-recordings of ten psychology students from an online university engaging in online learning tasks, and employed software to automatically detect eleven cognitive emotions. Preliminary results support and extend prior studies, illustrating how exploring cognitive emotions in real time can inform the development and success of academic e-learning interventions aimed at monitoring and promoting students' wellbeing

Cognitive Emotions in E-Learning Processes and Their Potential Relationship with Students’ Academic Adjustment

In times of growing importance and emphasis on improving academic outcomes for young people, their academic selves/lives are increasingly becoming more central to their understanding of their own wellbeing. How they experience and perceive their academic successes or failures, can influence their perceived self-efficacy and eventual academic achievement. To this end, ‘cognitive emotions’, elicited to acquire or develop new skills/knowledges, can play a crucial role as they indicate the state or the “flow” of a student’s emotions, when facing challenging tasks. Within innovative teaching models, measuring the affective components of learning have been mainly based on self-reports and scales which have neglected the real-time detection of emotions, through for example, recording or measuring facial expressions. The aim of the present study is to test the reliability of an ad hoc software trained to detect and classify cognitive emotions from facial expressions across two different environments, namely a video-lecture and a chat with teacher, and to explore cognitive emotions in relation to academic e-self efficacy and academic adjustment. To pursue these goals, we used video-recordings of ten psychology students from an online university engaging in online learning tasks, and employed software to automatically detect eleven cognitive emotions. Preliminary results support and extend prior studies, illustrating how exploring cognitive emotions in real time can inform the development and success of academic e-learning interventions aimed at monitoring and promoting students’ wellbeing

17p13.1 microdeletion: Genetic and clinical findings in a new patient with epilepsy and comparison with literature

Array comparative genomic hybridization is now a powerful tool to investigate patients with multiple congenital abnormalities and intellectual/motor impairment, and genomic imbalances are identified in a growing number of children with intellectual disability. Deletions in the 17p13.1 region have been reported in patients with dysmorphic features and developmental delay but a consistent phenotype has yet to emerge. Here, we report on the diagnosis of a 17p13.1 microdeletion of 829 kb in an 8-year-old girl presenting with profound cognitive disability, psychomotor delay, facial dysmorphisms, and refractory epilepsy. This deletion comprises 44 genes, including 8 OMIM morbid genes. We discuss genetic, clinical, and epileptic features comparing our patient with those previously reported in the literature

Symptomatic and presumed symptomatic focal epilepsies in childhood: An observational, prospective multicentre study

none44noOBJECTIVE: To describe the clinical, neuropsychological, and psychopathologic features of a cohort of children with a new diagnosis of symptomatic or presumed symptomatic focal epilepsy at time of recruitment and through the first month. The selected population will be followed for 2-5 years after enrollment to investigate the epilepsy course and identify early predictors of drug resistance. METHODS: In this observational, multicenter, nationwide study, children (age 1 month-12.9 years) with a new diagnosis of symptomatic or presumed symptomatic focal epilepsy were consecutively enrolled in 15 Italian tertiary childhood epilepsy centers. Inclusion criteria were as follows: (1) diagnosis of symptomatic focal epilepsy due to acquired and developmental etiologies, and presumed symptomatic focal epilepsy; (2) age at diagnosis older than 1 month and 3 to 6 years, and >6 years. Clinical, electroencephalography (EEG), neuroimaging, and neuropsychological variables were identified for statistical analyses. RESULTS: Two hundred fifty-nine children were enrolled (116 female and 143 male). Median age: 4.4 years (range 1 month-12.9 years); 46.0% (n = 119) of children were younger than 3 years, 24% (61) from 3 to 6 years of age, and 30% (79) older than 6 years. Neurologic examination findings were normal in 71.8%. Brain magnetic resonance imaging (MRI) was abnormal in 59.9%. Children age ≤3 years experienced the highest seizure frequency in the first month after recruitment (p < 0.0001). Monotherapy in the first month was used in 67.2%. Cognitive tests at baseline revealed abnormal scores in 30%; behavioral problems were present in 21%. At multivariate analysis, higher chances to exhibit more than five seizures in the first month after epilepsy onset was confirmed for younger children and those with temporal lobe epilepsy. SIGNIFICANCE: In this prospective cohort study, an extensive characterization of epilepsy onset in children with symptomatic or presumed symptomatic focal epilepsies is reported in relation to the age group and the localization of the epileptogenic zone.noneVecchi, Marilena; Barba, Carmen; De Carlo, Debora; Stivala, Micol; Guerrini, Renzo; Albamonte, Emilio; Ranalli, Domiziana; Battaglia, Domenica; Lunardi, Giada; Boniver, Clementina; Piccolo, Benedetta; Pisani, Francesco; Cantalupo, Gaetano; Nieddu, Giuliana; Casellato, Susanna; Cappanera, Silvia; Cesaroni, Elisabetta; Zamponi, Nelia; Serino, Domenico; Fusco, Lucia; Iodice, Alessandro; Palestra, Filippo; Giordano, Lucio; Freri, Elena; De Giorgi, Ilaria; Ragona, Francesca; Granata, Tiziana; Fiocchi, Isabella; Bova, Stefania Maria; Mastrangelo, Massimo; Verrotti, Alberto; Matricardi, Sara; Fontana, Elena; Caputo, Davide; Darra, Francesca; Dalla Bernardina, Bernardo; Beccaria, Francesca; Capovilla, Giuseppe; Baglietto, Maria Pia; Gagliardi, Alessandra; Vignoli, Aglaia; Canevini, Maria Paola; Perissinotto, Egle; Francione, StefanoVecchi, Marilena; Barba, Carmen; DE CARLO, Debora; Stivala, Micol; Guerrini, Renzo; Albamonte, Emilio; Ranalli, Domiziana; Battaglia, Domenica; Lunardi, Giada; Boniver, Clementina; Piccolo, Benedetta; Pisani, Francesco; Cantalupo, Gaetano; Nieddu, Giuliana; Casellato, Susanna; Cappanera, Silvia; Cesaroni, Elisabetta; Zamponi, Nelia; Serino, Domenico; Fusco, Lucia; Iodice, Alessandro; Palestra, Filippo; Giordano, Lucio; Freri, Elena; De Giorgi, Ilaria; Ragona, Francesca; Granata, Tiziana; Fiocchi, Isabella; Bova, Stefania Maria; Mastrangelo, Massimo; Verrotti, Alberto; Matricardi, Sara; Fontana, Elena; Caputo, Davide; Darra, Francesca; Dalla Bernardina, Bernardo; Beccaria, Francesca; Capovilla, Giuseppe; Baglietto, Maria Pia; Gagliardi, Alessandra; Vignoli, Aglaia; Canevini, Maria Paola; Perissinotto, Egle; Francione, Stefan