52 research outputs found
Games for and by Teachers and Learners
With the advent of social media it is widely accepted that teachers and learners are not only consumers but also may have an active role in contributing and co-creating lesson materials and content. Paradoxically one strand of technology enhanced learning, i.e. game-based learning, aligns only slightly to this development. Games while there to experience, explore and collaborate are almost exclusively designed by professionals. Despite, or maybe because, games are the exclusive domain of professional developers, the general impression is that games require complex technologies and that games are difficult to organise and to embed in a curriculum. This chapter will make a case that games are not necessarily the exclusive domain of game professionals. Rather than enforcing teachers to get acquainted with and use complex, technically demanding games, we will discuss approaches that teachers themselves can use to build games, make use of existing games and even one step beyond use tools or games that can be used by learners to create their own designs, e.g. games or virtual worlds
Keep it simple : Lowering the Barrier for Authoring Serious Games
Background. Despite the continuous and abundant growth of the game market the uptake of serious games in
education has been limited. Games require complex technologies and are difficult to organise and to
embed in the curriculum.
Aim. This article explores to what extent game templates and game authoring processes can be designed that can
be easily adopted and adapted by teachers while only using openly available tools.
Method. It discusses the design and first evaluation of two game platforms: ARGUMENT, based on a wiki, and
ARLEARN, a toolkit based on openly available Google technologies. ARGUMENT is a text-based
game challenging students to take a position on a given topic. ARLEARN offers an explicit mobile and
virtual gameplay environment and a defined authoring process to create game scripts.
Results. ARGUMENT and ARLEARN have been evaluated in four small-scale studies, where educators
designed game scenarios and students played the resulting games.
Conclusions. The results indicate that both tools are useful instruments that can be operated by teachers to build
games and game-alike educational activities and, additionally, are a valuable step to gain experience
with serious games.SURFnet/Kennisnet (ARGUMENT, StreetLearn, ARLearn), UNHC
INCREASING THE WILLINGNESS TO COLLABORATE ONLINE: AN ANALYSIS OF SENTIMENT-DRIVEN INTERACTIONS IN PEER CONTENT PRODUCTION
We investigate mechanisms that trigger collaborative work behavior in online peer communities. We regard the collaboration among Wikipedia editors as a social process influenced by specific communication practices. We analyze and quantify the way Wikipedia editors communicate their feedback and support towards each othersβ work in form of sentiments and opinions, and explore to what extent this influences online trust among them. We show that peer content production in Wikipedia is influenced by sharing sentiments during discussions among editors. At the global level, sharing sentiments positively influences the level of online trust. We also find a significant difference in the amount of online trust among editors who share mainly positive or mainly negative sentiments. We further suggest that providing and receiving especially supportive feedback expressed in form of positive sentiments and opinions may be beneficial in terms of virtual teamwork
Recommended from our members
A literature review of the use of Web 2.0 tools in Higher Education
This review focuses on the use of Web 2.0 tools in Higher Education. It provides a synthesis of the research literature in the field and a series of illustrative examples of how these tools are being used in learning and teaching. It draws out the perceived benefits that these new technologies appear to offer, and highlights some of the challenges and issues surrounding their use. The review forms the basis for a HE Academy funded project, βPeals in the Cloudβ, which is exploring how Web 2.0 tools can be used to support evidence-based practices in learning and teaching. The project has also produced two in-depth case studies, which are reported elsewhere (Galley et al., 2010, Alevizou et al., 2010). The case studies focus on evaluation of a recently developed site for learning and teaching, Cloudworks, which harnesses Web 2.0 functionality to facilitate the sharing and discussion of educational practice. The case studies aim to explore to what extent the Web 2.0 affordances of the site are successfully promoting the sharing of ideas, as well as scholarly reflections, on learning and teaching
ΠΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· Π»Π΅ΠΊΡΠΈΠΊΠΈ Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠ³ΠΎ ΡΠ·ΡΠΊΠ° Π² Π²ΠΈΠΊΠΈΡΠ»ΠΎΠ²Π°ΡΡΡ ΠΈ Wordnet.
A quantitative analysis of the English lexicon was performed in the paper. The three electronic dictionaries are under examination: the English Wiktionary, WordNet, and the Russian Wiktionary. The quantity of English words and their meanings (senses) are calculated. The distribution of words for each part of speech, the quantity of monosemous and polysemous words and the distribution of words by number of meanings were calculated and compared across these dictionaries. The analysis shows that the average polysemy, the number and the distribution of word senses follow similar patterns in both expert and collaborative resources with relatively minor differences.Π ΡΠ°Π±ΠΎΡΠ΅ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· Π»Π΅ΠΊΡΠΈΠΊΠΈ Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠ³ΠΎ ΡΠ·ΡΠΊΠ° ΠΏΠΎ Π΄Π°Π½Π½ΡΠΌ ΡΡΡΡ
ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΡΡ
ΡΠ»ΠΎΠ²Π°ΡΠ΅ΠΉ: ΠΠ½Π³Π»ΠΈΠΉΡΠΊΠΎΠ³ΠΎ ΠΠΈΠΊΠΈΡΠ»ΠΎΠ²Π°ΡΡ, WordNet ΠΈ Π ΡΡΡΠΊΠΎΠ³ΠΎ ΠΠΈΠΊΠΈΡΠ»ΠΎΠ²Π°ΡΡ. Π‘ΡΠ°Π²Π½ΠΈΠ²Π°Π΅ΡΡΡ ΠΎΠ±ΡΡΠΌ ΡΠ»ΠΎΠ²Π°ΡΠ΅ΠΉ ΠΈ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΡΠ»ΠΎΠ² Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠ³ΠΎ ΡΠ·ΡΠΊΠ° ΠΏΠΎ ΡΠ°ΡΡΡΠΌ ΡΠ΅ΡΠΈ. ΠΡΠΈΠ²ΠΎΠ΄ΠΈΡΡΡ ΡΠΎΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠ΅ ΠΌΠ½ΠΎΠ³ΠΎΠ·Π½Π°ΡΠ½ΡΡ
ΡΠ»ΠΎΠ² ΠΈ ΡΠ»ΠΎΠ² Ρ ΠΎΠ΄Π½ΠΈΠΌ Π·Π½Π°ΡΠ΅Π½ΠΈΠ΅ΠΌ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΈΡ
ΡΠ»ΠΎΠ² ΠΏΠΎ ΡΠΈΡΠ»Ρ Π·Π½Π°ΡΠ΅Π½ΠΈΠΉ. ΠΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΡ ΠΏΠΎΠΊΠ°Π·ΡΠ²Π°ΡΡ, ΡΡΠΎ Π»ΠΈΠ½Π³Π²ΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ΅ΡΡΡΡΡ, ΡΠΎΠ·Π΄Π°Π½Π½ΡΠ΅ ΠΊΠ°ΠΊ ΡΠΊΡΠΏΠ΅ΡΡΠ°ΠΌΠΈ, ΡΠ°ΠΊ ΠΈ ΡΠ½ΡΡΠ·ΠΈΠ°ΡΡΠ°ΠΌΠΈ, ΠΏΠΎΠ΄ΡΠΈΠ½ΡΡΡΡΡ ΠΎΠ±ΡΠΈΠΌ Π·Π°ΠΊΠΎΠ½Π°ΠΌ
ΠΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· Π»Π΅ΠΊΡΠΈΠΊΠΈ ΡΡΡΡΠΊΠΎΠ³ΠΎ WordNet ΠΈ Π²ΠΈΠΊΠΈΡΠ»ΠΎΠ²Π°ΡΠ΅ΠΉ
A quantitative analysis of the Russian lexicon was performed in the paper. The thesaurus Russian WordNet and two electronic dictionaries are under examination: the Russian Wiktionary and the English Wiktionary. The quantity of Russian words and their meanings (senses) according to the parts of speech are compared. The distribution of words for each part of speech, the quantity of monosemous and polysemous words and the distribution of words by number of meanings were calculated and compared across these dictionaries. The analysis of the distribution of words by number of meanings revealed a problem that too few or no ambigous Russian words with the number of meanings more than 4 are presented in the English Wiktionary (in comparison with the Russian Wiktionary). The analysis shows that the average polysemy, the number and the distribution of word senses follow similar patterns in both expert and collaborative resources with relatively minor differences.Π ΡΠ°Π±ΠΎΡΠ΅ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· Π»Π΅ΠΊΡΠΈΠΊΠΈ ΡΡΡΡΠΊΠΎΠ³ΠΎ ΡΠ·ΡΠΊΠ° ΠΏΠΎ Π΄Π°Π½Π½ΡΠΌ ΡΠ΅Π·Π°ΡΡΡΡΠ° Π ΡΡΡΠΊΠΈΠΉ WordNet ΠΈ Π΄Π²ΡΡ
ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΡΡ
ΡΠ»ΠΎΠ²Π°ΡΠ΅ΠΉ (Π ΡΡΡΠΊΠΈΠΉ ΠΠΈΠΊΠΈΡΠ»ΠΎΠ²Π°ΡΡ ΠΈ ΠΠ½Π³Π»ΠΈΠΉΡΠΊΠΈΠΉ ΠΠΈΠΊΠΈΡΠ»ΠΎΠ²Π°ΡΡ). Π‘ΡΠ°Π²Π½ΠΈΠ²Π°Π΅ΡΡΡ ΠΎΠ±ΡΡΠΌ ΡΠ»ΠΎΠ²Π°ΡΠ΅ΠΉ ΠΈ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΡΠ»ΠΎΠ² ΡΡΡΡΠΊΠΎΠ³ΠΎ ΡΠ·ΡΠΊΠ° ΠΏΠΎ ΡΠ°ΡΡΡΠΌ ΡΠ΅ΡΠΈ. ΠΡΠΈΠ²ΠΎΠ΄ΠΈΡΡΡ ΡΠΎΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠ΅ ΠΌΠ½ΠΎΠ³ΠΎΠ·Π½Π°ΡΠ½ΡΡ
ΡΠ»ΠΎΠ² ΠΈ ΡΠ»ΠΎΠ² Ρ ΠΎΠ΄Π½ΠΈΠΌ Π·Π½Π°ΡΠ΅Π½ΠΈΠ΅ΠΌ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΡΡΡΡΠΊΠΈΡ
ΡΠ»ΠΎΠ² ΠΏΠΎ ΡΠΈΡΠ»Ρ Π·Π½Π°ΡΠ΅Π½ΠΈΠΉ. ΠΠ½Π°Π»ΠΈΠ· ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΡΠΈΡΠ»Π° Π·Π½Π°ΡΠ΅Π½ΠΈΠΉ Π²ΡΡΠ²ΠΈΠ» ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ ΠΠ½Π³Π»ΠΈΠΉΡΠΊΠΎΠ³ΠΎ ΠΠΈΠΊΠΈΡΠ»ΠΎΠ²Π°ΡΡ β ΠΎΡΡΡΡΡΡΠ²ΠΈΠ΅ ΠΈΠ»ΠΈ Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½Π°Ρ ΠΏΡΠΎΡΠ°Π±ΠΎΡΠΊΠ° ΠΌΠ½ΠΎΠ³ΠΎΠ·Π½Π°ΡΠ½ΡΡ
ΡΡΡΡΠΊΠΈΡ
ΡΠ»ΠΎΠ² Ρ ΡΠΈΡΠ»ΠΎΠΌ Π·Π½Π°ΡΠ΅Π½ΠΈΠΉ Π±ΠΎΠ»ΡΡΠ΅ ΡΠ΅ΡΡΡΡΡ
(ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ ΡΠΎ ΡΠ»ΠΎΠ²Π°ΠΌΠΈ Π ΡΡΡΠΊΠΎΠ³ΠΎ ΠΠΈΠΊΠΈΡΠ»ΠΎΠ²Π°ΡΡ). ΠΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΡ ΠΏΠΎΠΊΠ°Π·ΡΠ²Π°ΡΡ, ΡΡΠΎ Π»ΠΈΠ½Π³Π²ΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ΅ΡΡΡΡΡ, ΡΠΎΠ·Π΄Π°Π½Π½ΡΠ΅ ΡΠ½ΡΡΠ·ΠΈΠ°ΡΡΠ°ΠΌΠΈ, Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΡΡΡ ΡΠ΅ ΠΆΠ΅ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΠ½ΠΎΡΡΠΈ, ΡΡΠΎ ΠΈ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π½ΡΠ΅ ΡΠ»ΠΎΠ²Π°ΡΠΈ
Framework for collaborative knowledge management in organizations
Nowadays organizations have been pushed to speed up the rate of industrial transformation to high value products and services. The capability to agilely respond to new market demands became a strategic pillar for innovation, and knowledge management could support organizations to achieve that goal. However, current knowledge management approaches tend to be over complex or too academic, with interfaces difficult to manage, even more if cooperative handling is required. Nevertheless, in an ideal framework, both tacit and explicit knowledge management should be addressed to achieve knowledge handling with precise and semantically meaningful definitions. Moreover, with the increase of Internet usage, the amount of available information explodes. It leads to the observed progress in the creation of mechanisms to retrieve useful knowledge from the huge existent amount of information sources. However, a same knowledge representation of a thing could mean differently to different people and applications.
Contributing towards this direction, this thesis proposes a framework capable of gathering the knowledge held by domain experts and domain sources through a knowledge management system and transform it into explicit ontologies. This enables to build tools with advanced reasoning capacities with the aim to support enterprises decision-making processes. The author also intends to address the problem of knowledge transference within an among organizations. This will be done through a module (part of the proposed framework) for domainβs lexicon establishment which purpose is to represent and unify the understanding of the domainβs used semantic
- β¦