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Alteration of the forgetting curve through repetition according to Ebbinghaus (1885) and estimations from Paul (2007)

Alteration of the forgetting curve through repetition according to Ebbinghaus (1885) and estimations from Paul (2007)

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Conference Paper
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Repetition fosters learning. And games take the dullness from repetition. Hence, learning games promise to be a valuable addition to any learning media portfolio. But how do learners know which content they should learn at a given time in order to get the best learning results? This paper introduces an approach for mobile learning games that eases...

Citations

... While the roots of spaced repetition originate from learning with paper-based flashcards, there are already different sophisticated computer-based algorithms available, which determine the ideal repetition intervals by evaluating the learner's performance in past repetitions and combining this with other factors like the number of already done repetitions. We have used one of the most widely spread spaced repetition algorithms, "SM2", in earlier work [5] to research the possibilities of combining the long-term effect of spaced repetition learning with the motivating and immersing effects of learning games. The goal is to create a framework for iOS-based mobile learning games that enhances them with spaced repetition and content selection algorithms for a bigger focus on long-term retention. ...
... It calculates the learning intervals based on the performance of the learners on a given learning item in the past, the number of times this item has already been presented and the current learning performance. In an early stage of our research, we found out that the SM2 algorithm can be used well in learning games [5]. In addition to that, there also has to be an auxiliary algorithm in order to take over the content selection if the learner should decide to play the same content repeatedly in the same learning session and therefore outside the calculated intervals. ...
... In our research we want to combine spacing with the motivating and immersing effect of learning games. In earlier research [3] we have already shown that both approaches play well together if there are made some adjustments. For example, we have already found out that using the strictly time-based SM2 algorithm alone may lead to corrupted calculation values if the learners decide to play the game several rounds in a row [4]. ...
Article
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Especially software running on mobile devices does increasingly rely on contextual information such as time and location. And whenever a software product is affected by context, this context has to be replicated for testing and debugging. This paper introduces an external context manipulation interface for a previously developed learning item scheduler. The scheduler determines when to present a learning item in a learning game based on previous interaction in order to maximize learning efficiency and is based on psychological models. As inter-presentation-intervals can be in the range of days to months, system testing cannot be conducted in a conventional manner. Hence, virtual time hops can be used to fast forward to any specific point in virtual time which would make the software act like it was system time. The approach has shown to be a valuable debugging and testing aid and can be extended for other contextual information sources.
... In our research we want to combine spacing with the motivating and immersing effect of learning games. In earlier research [3] we have already shown that both approaches play well together if there are made some adjustments. For example, we have already found out that using the strictly time-based SM2 algorithm alone may lead to corrupted calculation values if the learners decide to play the game several rounds in a row [4]. ...
Conference Paper
Full-text available
Especially software running on mobile devices does increasingly rely on contextual information such as time and location. And whenever a software product is affected by context, this context has to be replicated for testing and debugging. This paper introduces an external context manipulation interface for a previously developed learning item scheduler. The scheduler determines when to present a learning item in a learning game based on previous interaction in order to maximize learning efficiency and is based on psychological models. As inter-presentation-intervals can be in the range of days to months, system testing cannot be conducted in a conventional manner. Hence, virtual time hops can be used to fast forward to any specific point in virtual time which would make the software act like it was system time. The approach has shown to be a valuable debugging and testing aid and can be extended for other contextual information sources.
... This is also the algorithm we are going to use in our framework. However, since we already found out (Schimanke, 2013) that a spaced repetition algorithm alone may not be sufficient enough due to too many repetitions of the same learning content in a very short time, especially when there is only limited content available, we have also developed an auxiliary algorithm, called the FS (Follow-up Sequence) algorithm. This algorithm is responsible for content selection when the learner decides to play the game several times in a row, leading to early repetitions, which are not in line with the intervals calculated by the spaced repetition algorithm. ...
Conference Paper
Full-text available
Spaced repetition is an algorithmic strategy for selecting learning content based on the learner's previous interaction with the mentioned content. Presentation intervals are longer for items presented more often and already learned. But even these items are presented in order to avoid forgetting them over time. Hence spaced repetition is an ideal tool for avoiding forgetting of once learned content. Integrating this content selection strategy in (mobile) learning games does not only foster learning in a more efficient way, it also keeps learners/players more motivated as their performance increases over time. This paper discusses strategies for adding spaced repetition content selection to existing games to combine already successful learning games with this promising content selection strategy.
... Values used to determine the intervals include the number of times a learning item was previously accessed and the learner's performance on these previous interactions with that item. While spaced repetition learning software has become popular for simple learning tasks, such as flash cards used for studying vocabulary, it was shown that those algorithms could also be used for content selection and repetition scheduling in mobile learning games[5]. When properly designed, those games are widely seen as a promising way to distribute learning content to the learners in a motivating and engaging manner[6]. ...
Conference Paper
Full-text available
Spaced repetition learning is an approach for choosing the most efficient intervals between rehearsing learning content. Typically used for tasks like learning vocabulary it also offers great potential for content selection in learning games. Learning games do, however differ from classic spaced repetition learning approaches in that content is not only accessed when indicated by a spaced repetition scheduling algorithm but also when the users simply want to play the game or when they decide to play the game multiple times in a row. In these cases, short term memory effects might mask learning effects in user performance, leading to faulty inputs to the calculation of spaced repetition interval lengths. This paper reviews current research literature on the interaction of short term and long term memory in order to determine how short term memory effects can be coped with in the context of spaced repetition based learning games.
... One of the most widely spread algorithms is called " SM2 " , which was originally developed for learning with learning cards. However, in earlier research (Schimanke, 2013) we have already shown that it can also be adopted to be used in game-based learning and have therefore decided to use it in the learning game for this evaluation. Those learning games are widely seen as a way to distribute learning content in a motivating and engaging manner to the learners (Gee, 2003). ...
Conference Paper
Full-text available
Forgetting is one of the common problems in learning. While students might grasp an idea when it is being presented in a lecture they might only vaguely remember it two weeks later and they might have completely forgotten it when the final exams are due. One way out of this is concentrated learning right before the test, also called cramming, massing or bulimic learning in order to highlight the fact that knowledge is only retained for a very brief time. Another approach is spaced repetition learning in which learning items are presented in growing intervals in such a way that the students never really forget and that knowledge is reinforced with each repetition. This paper presents a study in which learning items were incorporated into a mobile learning game in order to make the spaced repetition approach as transparent as possible to the students. The game was used in a database lecture and students reported good usability and learning efficiency.
... The calculation of those ideal intervals can already be done by sophisticated algorithms which try to determine them by judging the learner's performance in past presentations and combining it with other factors like the number of repetitions. This approach, which was originally developed for learning with learning cards, can also be adopted in game-based learning as we have shown in [3]. One of the most widely spread algorithms is delivered by SuperMemo and is called "SM2". ...
... In this case, the values used by the SM2 algorithm to schedule the next regular repetition might get corrupted which also bears the potential to affect the whole idea behind spaced repetitions. We have therefore developed the FS algorithm, which works in a round-based manner in contrast to the time-based SM2 algorithm [3]. The FS algorithm determines in a way similar to the SM2 algorithm, which items should be repeated more frequently than others while avoiding repetitions of the same item back to back. ...
... This algorithm is responsible for scheduling the repetitions of each learning content item based on the research of the spacing effect by Hermann Ebbinghaus [1]. The other algorithm is the FS algorithm which we have introduced in an earlier paper [3] and which is responsible for content selection in scenarios where learners decide to play several rounds of the game in a row or when they play it at unscheduled times. ...
Conference Paper
Full-text available
When programs get big enough to be called software, they need an architecture. An architecture helps organizing a software's structure so that it is easier to maintain and so that parts of it can be re-used in similar circumstances. When spaced repetition based mobile learning is concerned, re-use is crucial. Spaced repetition learning is an approach that schedules presentation of learning content based on psychological models. Paired with learning games, it can be used to control the flow of the game so that learning content is presented in the most efficient manner. In order to achieve this, the game and the spaced repetition model have to act in a highly interleaved manner. However, the spaced repetition model remains the same, regardless of the game at hand. A useful architecture would design interaction between the spaced repetition model and a game so that developers can focus on the game part and use a minimal interface to turn a simple learning game into a spaced repetition learning game. As space repetition relies on calculated presentation intervals, mobile devices are an optimal platform since they allow for learning anytime. However, mobile devices come with unique constraints that have to be considered when conceiving an architecture. This paper discusses possible software architectures for spaced repetition learning games on the iOS platform as well as architecturally relevant details of spaced repetition learning.
... The calculation of those ideal intervals can already be done by sophisticated algorithms which try to determine them by judging the learner's performance in past presentations and combining it with other factors like the number of repetitions. This approach, which was originally developed for learning with learning cards, can also be adopted in game-based learning as we have shown in [3]. One of the most widely spread algorithms is delivered by SuperMemo and is called "SM2". ...
... In this case, the values used by the SM2 algorithm to schedule the next regular repetition might get corrupted which also bears the potential to affect the whole idea behind spaced repetitions. We have therefore developed the FS algorithm, which works in a round-based manner in contrast to the time-based SM2 algorithm [3]. The FS algorithm determines in a way similar to the SM2 algorithm, which items should be repeated more frequently than others while avoiding repetitions of the same item back to back. ...
... This algorithm is responsible for scheduling the repetitions of each learning content item based on the research of the spacing effect by Hermann Ebbinghaus [1]. The other algorithm is the FS algorithm which we have introduced in an earlier paper [3] and which is responsible for content selection in scenarios where learners decide to play several rounds of the game in a row or when they play it at unscheduled times. ...
... While there are already mobile implementations of these algorithms for vocabulary learning, it has not yet been used in game-based learning. We have already introduced two prototype mobile learning games which are based on the SM2 algorithm to schedule repetition for certain content at the optimal intervals (Schimanke et al., 2013a and2013b). ...
... Depending on the respective learning topic, there might be a limited amount of content which often leads the user to play several rounds of the game in a row. As described in Schimanke et al. (2013a) this will corrupt the spaced repetition concept since the algorithmically calculated time is not elapsed before the learner starts the next repetition. This might also affect the playing behavior. ...
... Due to a usually better performance because of the short term memory effect, this would lead to a next scheduled repetition which is too far in the future and thus compromises the spaced repetition approach. Therefore we have developed the FS algorithm (Schimanke et al., 2013a) which is round-based and which takes over the content selection when the user decides to play one or more rounds after the initial, scheduled one. After the SM2 algorithm has selected the appropriate content after starting the game and rescheduled the next repetition based on the learners' performance, the FS algorithm is in charge to mimic the SM2-concept of ranking learning content by the level the learners already remember it in a round-based manner for the remainder of that game session. ...
Conference Paper
Full-text available
Learning games are an ideal vessel for many kinds of learning content. Playful interaction with the subject matter makes the human mind more receptive and thus learning itself more effective. Well designed games also come with an addictive game-play that makes users want to play the game over and over. This is intended in fun games but it can be counterproductive in learning games as users spend time with content they are already proficient with while they could use this time to learn other less familiar content. Spaced-repetition-learning is a learning approach that helps to improve retention with a minimal number of repetitions. It uses an algorithm based on psychological models to determine when to present a content item. This paper discusses design considerations from both the game-based and the spaced-repetition perspective to explore how the efficiency of spaced-repetition-learning can be combined with the fun and effectiveness of game-based learning.
... In an earlier paper we have already introduced a way to transfer the SM2 algorithm for scheduling spaced repetitions to game-based learning [9]. The app "Where is my Box?" was intended to show how spaced repetition language learning can be done with a mobile learning game. ...
Conference Paper
Full-text available
Learning requires repetition. Spaced repetition algorithms are aimed at reducing the number of times a learning item has to be accessed by the learner by scheduling item presentation based on psychological models. These models take into account learner performance on previous interactions with the learning item and the rate at which humans forget what they have learned. In recent years, spaced repetition learning software has become popular for simple learning tasks like flash cards used for learning vocabulary. This paper presents a prototype application that extends the spaced repetition learning approach to more complex content like the kind usually found in learning games. One major difference between this content and flash cards is that learning games usually contain a number of different tasks that convey the same underlying concept categories. To complicate matters, one task might even be classified as belonging to a number of independent or orthogonal categories. This paper explores how these categories can be modeled on the basis of a mobile game designed for training in the field of relational databases. We have chosen a mobile approach to leverage it’s anytime/anyplace availability which allows a more precise scheduling by the spaced repetition algorithm.