November 15, 2010 in Education (E)
[prMac.com] Dublin, Ireland - Mindconnex Learning today announced the upcoming availability of its 'Shakespeare In Bits' series on the Mac App Store. The company plans to make its popular 'Shakespeare In Bits: Romeo & Juliet' title available for the Mac App store launch, and will follow-up closely with its upcoming 'Macbeth' title. Both plays will feature a newly-developed OSX-native version of the Shakespeare In Bits player that will harness the unique capabilities of the Mac.
The iPad and iPhone editions of 'Shakespeare In Bits: Romeo & Juliet' are currently being featured on the US App Store as part of its 'American Education Week' feature. Released in May 2010 and featuring the voice talents of Michael Sheen (30 Rock, Frost/Nixon) and Kate Beckinsale (The Aviator, Underworld) as the tragic couple, 'Romeo & Juliet' has achieved over 10,000 downloads of its Full and Lite editions for iOS devices, and continues to prove popular with students and educators alike. It has been featured several times on App Store home pages worldwide, and was chosen by Apple as 'App of the Week' in September 2010 in the UK and Ireland.
"We're excited about the Mac App store, and we see it as an ideal distribution platform for Shakespeare In Bits," said Michael Cordner, director and lead technologist of Mindconnex Learning. "Our new Mac version nicely compliments the existing iPhone and iPad versions, and provides new options for teachers looking for a compelling way to present Shakespeare to their classes."
'Shakespeare In Bits' is a new, integrated approach to Shakespeare Studies that promotes quicker learning, deeper understanding, and greater appreciation of Shakespeare's plays. Leveraging the full capabilities of iOS devices and the Mac platform, it presents an interactive, unabridged version of the play's text alongside a fully animated presentation. It also includes a full range of innovative study features, including dynamic translations of difficult terms, full synopses and study notes for each section, and a character map highlighting the relationships between the characters.
The next title in the series, 'Shakespeare In Bits: Macbeth', will be available for the iPad and iPhone around the end of November/Early December 2010, as well as for the Mac App Store when it becomes available. It features Stephen Dillane (King Arthur, The Hours) as Macbeth and Fiona Shaw (Harry Potter) as Lady Macbeth. It will present two-and-a-half hours of full animation and audio, along with the complete play text and the same range of helpful learning features pioneered in 'Romeo & Juliet'.
Shakespeare In Bits: Romeo & Juliet for Mac Product Features:
* The unabridged original play text, broken into easily digested 'bits'
* Three hours of animation with full audio, (Audio provided by Naxos Audiobooks)
* A new mac-exclusive subtitle feature which shows the currently spoken lines of text in the animation window.
* Complete notes, summaries, and analyses for each section
* A unique in-line translation system for obscure words and phrases
* Biographies for each character, accessed from the main play or through the cast browser
* A character relationship map, demonstrating key relationships in the play
Pricing and Availability:
"Romeo & Juliet" and "Macbeth" for Mac will retail for $24.99 (USD) exclusively on the Mac App Store (with equivalent local pricing in other currencies). The iPhone/iPod touch and iPad "Romeo & Juliet" apps retail for $7.99 (USD) and $14.99 respectively (with equivalent local pricing in other currencies), exclusively on the App Store.
Mindconnex Learning Limited is an interactive, educational software development company based in Dublin, Ireland. It employs 5 educational software and developer professionals. It was founded in 2008 to create genuinely innovative digital learning tools for today's students and teachers. Copyright (C) 2008-2010 Mindconnex Learning Limited. All Rights Reserved. Apple, the Apple logo, iPhone, iPod and iPad are registered trademarks of Apple Inc. in the U.S. and/or other countries.